steps towards the 2000-watt society 070729 - final

DISS. ETH NO. 17314

INTERMEDIATE STEPS TOWARDS THE 2000-

WATT SOCIETY IN SWITZERLAND:

AN ENERGY-ECONOMIC SCENARIO ANALYSIS

A dissertation submitted to

ETH ZÜRICH

for the degree of

Doctor of Science

presented by

Thorsten Frank Schulz

Dipl.-Ing., University of Stuttgart, Germany

born 13.01.1977

citizen of Germany

accepted on recommendation of

Prof. Dr. Alexander Wokaun, examiner

Prof. Dr. Konrad Hungerbühler, co-examiner

Mr. Socrates Kypreos, co-examiner

Zürich 2007

iii

What gets us into trouble is not what we don't know.

It's what we know for sure that just ain't so.

Mark Twain

v

Acknowledgment

I want to thank all those people who have helped in achieving all that has been

reflected in this thesis. I want to thank them for their direct and indirect support

throughout my 3 ½ years stay that the Paul Scherrer Institute (PSI). For me it has

been a privilege to be a member of the PSI Energy Economics Group. First of all, I

would like to thank my direct supervisor and Head of the Energy Economics Group

Socrates Kypreos for giving me the opportunity to join his group, for introducing me

to the secrets of MARKAL and for sharing his enormous experience in the complex

area of energy modelling. I am sincerely thankful to my doctoral advisor Prof. Dr.

Alexander Wokaun, for accepting me as a PhD student, for valuable discussions, for

his guidance and support to this work. I also want to thank Prof. Dr. Konrad

Hungerbühler, who kindly agreed to co-examine this thesis and provided me with

helpful suggestions and comments.

My very special thanks goes to Dr. Leonardo Barreto for numerous fruitful

discussions, for his feedbacks, directions, encouragements and his careful reading of

various reports, papers as well as this work. I greatly benefited from inputs and

discussions with Dr. Stefan Hirschberg, Head of the Laboratory for Energy Systems

Analysis. I am deeply indebted to Dr. Martin Jakob from the Centre for Energy Policy

and Economics (CEPE) for providing me detailed information on marginal-cost

curves and reduction potentials of dwelling houses. I want to thank Dr. Nico Bauer,

for his constructive critique and introduction to MATLAB and CPLEX. I also like to

thank my friends as well as all present and past members of the Energy Economics

Group who contributed in different ways to complete this work: Timur Gül, Dr. Daniel

Krzyzanowski, Dr. Bertrand Magné, Dr. Peter Rafaj, Ulrich Reiter, Dr. Michael

Spielmann. I am grateful to Pasquale Lauria, Ingo and Ulrich Löffler, Florian Nagel

and Jürgen Schuol for being around when I needed them and for sharing the funnier

moments of our lives. Finally I want to thank Dr. Mark Howells for advising me to join

the Energy Economics Group.

The financial support of the Swiss National Science Foundation in the context of the

NCCR-Climate project is gratefully acknowledged.

I dedicate this work to my family.

vii

Table of contents

Acknowledgment .........................................................................................................v

Table of contents ....................................................................................................... vii

Nomenclature/abbreviations ........................................................................................x

Abstract .................................................................................................................... xiii

Kurzfassung...............................................................................................................xv

1 Introduction .......................................................................................................... 1

1.1 Motivation .................................................................................................. 1

1.2 Scope of the analysis................................................................................. 2

1.3 Methodology .............................................................................................. 3

1.4 Structure of the thesis................................................................................ 4

2 The 2000-Watt society ......................................................................................... 6

2.1 Description of the 2000-Watt society ......................................................... 6

2.2 Literature review ........................................................................................ 7

2.3 The 2000-Watt society from today’s perspective ......................................11

2.4 Some energy definitions ...........................................................................11

3 Defining the baseline...........................................................................................13

3.1 Structure and main assumptions of the Swiss-MARKAL model (SMM)....13

3.2 Renewable energy potential and nuclear energy......................................15

3.3 Energy and emission balances of the baseline scenario ..........................18

3.3.1 Primary-energy balances .................................................................18

3.3.2 Final-energy balances ......................................................................20

3.3.3 Electricity production and consumption ............................................22

3.3.4 CO2 emissions..................................................................................24

3.4 Description of the residential sector..........................................................25

3.4.1 Base year calibration........................................................................26

3.4.2 Future projection ..............................................................................27

3.5 Description of the transportation sector ....................................................48

3.5.1 Base year calibration........................................................................49

3.5.2 Future projection ..............................................................................53

3.5.3 Detailed final-energy consumption ...................................................56

viii

4 Evaluating intermediate steps towards the 2000-Watt society ............................59

4.1 Primary-energy balances of the 3500-Watt society ..................................59

4.2 The role of end-use sectors in the 3500-Watt society...............................63

4.3 Importance of alternative future scenarios with carbon (CO2) restrictions 74

4.4 Energy balances of the 3500-Watt society with a 10% per decade CO2

restrictions ................................................................................................79

4.5 Conclusions ..............................................................................................90

5 Complementary analyses....................................................................................92

5.1 Sensitivity analysis on discount rates .......................................................93

5.2 The influence of fuel-cells price and stack sizes on hydrogen cars ..........94

5.3 The influence of renewable energy-conversion equivalents on the

production of electricity .............................................................................95

5.4 Partial equilibrium with elastic demands ...................................................98

5.5 Assessing wood-based synthetic-fuel technologies................................101

5.5.1 Oil price sensitivity analysis............................................................103

5.5.2 Oil price and subsidy sensitivity analysis of the methanation plant 107

5.5.3 Investment cost sensitivity analysis of the methanation plant ........108

5.5.4 The comparison of Fischer-Tropsch and methanation plants.........110

5.5.5 Remarks on the methantion plant ..................................................111

6 Conclusions and recommendations ..................................................................113

6.1 The 2000-Watt society: Results from the Swiss MARKAL model ...........113

6.1.1 Primary energy consumption and final energy implications............114

6.1.2 Technological change and CO2 emissions.....................................116

6.1.3 Additional total system costs ..........................................................119

6.1.4 The influence of discount rates ......................................................120

6.1.5 Partial equilibrium with elastic demands.........................................121

6.2 Lessons learned .....................................................................................121

6.3 Outlook on future research .....................................................................122

References ..............................................................................................................124

List of figures ...........................................................................................................133

List of tables ............................................................................................................137

Appendix 1: Technological description of room-heating technologies .....................138

ix

Appendix 2: Technological description of passenger cars .......................................139

Appendix 3: Biomass technology description ..........................................................140

Appendix 4: Final-energy calibration of the Swiss MARKAL model (SMM) to SFOE

and IEA statistic of the year 2000......................................................................141

Appendix 5: Oil-price sensitivity...............................................................................142

Appendix 5.1: Primary-energy balances..................................................................144

Appendix 5.2: Final-energy balances ......................................................................148

Appendix 5.3: Electricity balance.............................................................................162

Appendix 5.4: Total system costs ............................................................................164

Curriculum Vitae ......................................................................................................170

x

Nomenclature/abbreviations

Bio-SNG Synthetic natural gas from biomass (wood)

bvkm Billion Vehicel Kilometres

bvkm / a Billion Vehicle Kilometres per Year

CEPE Centre for Energy Policy and Economy

CH4 Methane

CHP Combined heat and power

CORE Federal Energy Research Commission

CO2 Carbon Dioxide

CRF Capital Recovery Factor

DETEC Department of the Environment, Transport, Energy and Communications

DMD Demand

dr discount rate

EAWAG Swiss Federal Institute of Aquatic Science and Technology

EEG Energy Economics Group at the Paul Scherrer Institute

EMPA Swiss Federal Laboratries for Materials Testing and Research

eq. Equivalent

ERFA Energy Reference Floor Area - Sum of the Heated Floor Areas

ETH Swiss Federal Institute of Technology

ETSAP Energy Technology Systems Analysis Programme

FC Fuel Cell

FE Final Energy

FT Fischer-Tropsch

GDP Gross Domestic Product

GEST Swiss Overall Energy Statistics

GHG Greenhouse Gas

H2 Hydrogen

ICE Internal Combustion Engine

IEA International Energy Agency

IPCC Intergovernmental Panel on Climate Change

kW kilo-Watt (1000 Watt)

Lt Litre

m meter

xi

MARKAL Market Allocation

MC Marginal Cost

MFH Multi-Family Houses

Mt Million tones

N2O Nitrous oxide

O&M Operation and Maintenance

P Power [W/s]

PE Primary Energy

PEC Primary Energy per Capita

PJ Peta Joule

PSI Paul Scherrer Institute

RES Reference Energy System

RC1 Residential Cooling

RCD Residential Cloth Drying

RCW Residential Cloth Washing

RDW Residential Dish Washing

REA Residential Other Electric

RH Room Heating

RH1 Room-Heating Single-Family Houses existing building

RH2 Room-Heating Single-Family Houses new building

RH3 Room-Heating Multi-Family Houses existing buildings

RH4 Room-Heating Multi-Family Houses new buildings

RHW Residential Hot Water

RK1 Residential Cooking

RL1 Residential Lighting

RRF Residential Refrigeration

s second

SATW Swiss Academy of Engineering Science

SFH Single-Family Houses

SFOE Swiss Federal Office of Energy

SMM Swiss MARKAL model

TAD Domestic Aviation

TAI International Aviation

TP Time Period

xii

TRB Bus

TRM Trucks

TRT Passenger Cars

TRW Two Wheelers

TTP Rail

TWD Domestic Navigation

TWI International Navigation

UED Useful Energy Demand

v velocity [m/s]

W Watt

W/Cap Watt per Capita

WSL Swiss Federal Institute for Forest, Snow and Landscape Research

xiii

Abstract

In future, the sustainable development of the Swiss energy sector under the umbrella

of the 2000-Watt society is of major interest. Thereby the vision of a primary energy

per capita (PEC) consumption of only 2000 Watts should ideally fulfil many targets

such as improving the energy efficiency of the Swiss energy sector, reducing the

dependency on fossil energy carriers, promoting renewable energies and contributing

to the climate-change strategies. This dissertation aims at finding realistic targets for

the vision of the 2000-Watt society until 2050. It looks at various combinations of

PEC and CO2 targets and estimates the additional costs to be paid by the Swiss

society. The assessment is conducted with the Swiss MARKAL (MARKet ALlocation)

model. Swiss MARKAL represents a bottom-up energy-systems model that provides

a detailed representation of energy supply and end-use technologies. It projects

future technology investments and offers an integrated analysis of primary,

secondary, final and end-use energy for Switzerland.

The analysis reveals that the 2000-Watt society should be seen as a long-term goal.

In the year 2000, the PEC consumption was about 5000 Watts per person with 44.4

Mt of energy-related CO2 emissions. For all contemplated scenarios independent of

the oil price, a PEC consumption of 3500 Watts per capita is feasible in the year

2050. However, strong PEC consumption targets can reduce CO2 emissions to an

equivalent of 5 % per decade at maximum. For stronger CO2 emission-reduction

goals, corresponding targets must be formulated explicitly. The opposite approach of

tightening only CO2 targets will reduce the PEC consumption to values between 4900

and 4500 Watts per capita, depending on the oil price in the year 2050. Therefore, a

CO2 reduction alone does not sufficiently move into the direction of a 2000-Watt

society.

The major changes required concern energy-transformation and energy-demand

technologies. Electricity will play, more than ever, an important role in a service-

oriented society in the future. The production of electricity will increase from a today’s

level of 57 TWh to at least 70 - 85 TWh in 2050. Dwelling houses and the vehicle

fleet have to undergo a complete transformation until 2050 if we want to reduce

energy consumption and lower CO2 emissions. Less heat consumption and more

heat pumps as well as natural gas and hydrogen engine drives for cars would be the

choice in the future.

xiv

Such a transformation comes at a cost; even intermediate steps are associated with

sizeable expenses. At an oil price of 75 US$2000/bbl in 2050, the additional costs to

reach a 3500-Watt society amount to about 20 billion US$2000 (~33 billion CHF2000). A

Kyoto-for-ever target (i.e. 5 % CO2 reduction per decade) costs about 15 billion

US$2000 (~25 billion CHF2000) or 5 billion US$2000 (~8 billion CHF2000) less. If a 10 %

CO2 reduction per decade is envisaged additional to the 3500 Watts per capita

target, the extra costs amount to about 40 billion US$2000 (~67 billion CHF2000),

despite potentially associated technological and cost synergies. If the main argument

in favour of the 3500-Watt society was CO2 reduction, then the PEC target is

questionable.

By following pure energy-efficiency strategies with the only objective to reduce the

PEC consumption, we do not meet up to possibly-desired climate-change strategies.

A moderate fossil import dependency and the enhanced use of renewable energies

are supported mainly by CO2 reduction targets. Despite the fact that this study shows

only potential cost-effective pathways but does not unfold necessary incentives of

how to adopt these pathways, the study clearly shows: The transition of the current

energy system is difficult and all targeted changes will not happen on their own. We

need goal-oriented measures from decision-makers such that people change their

behaviour and invest in more efficient and cleaner technologies rather sooner than

later.

Keywords: 2000-Watt society, MARKAL, Switzerland, energy, economy

xv

Kurzfassung

Eine nachhaltige Entwicklung des schweizerischen Energiesystems mit der Vision

einer 2000-Watt Gesellschaft könnte in der Zukunft von grossem Interesse sein. Die

Vision einer 2000-Watt Gesellschaft (also einer Gesellschaft mit einem

Primärenergieverbrauch von 2000 Watt pro Kopf) sollte idealerweise der Erreichung

mehrerer Ziele dienen: der Steigerung der Energieeffizienz des schweizerischen

Energiesektors, der Minderung der Abhängigkeit von fossilen Energieträgern und der

Unterstützung von erneuerbaren Energien und Klimaschutzzielen.

Die vorliegende Studie versucht, realistische Ziele für die Vision der 2000-Watt

Gesellschaft bis in das Jahr 2050 aufzuzeigen. Dazu werden verschiedene

Kombinationen von Primärenergie- und CO2-Minderungszielen untersucht, sowie

anfallende zusätzlichen Kosten berechnet, welche von der Gesellschaft für die

Erreichung eines jeden Zieles getragen werden müssen. Die Ergebnisse der

Dissertation wurden mit Hilfe des Energiesystemmodells Swiss MARKAL (MARKet

ALLocation) erarbeitet. Swiss MARKAL ist ein bottom-up (von unten nach oben

aufbauendes) Energiesystemmodell für die Schweiz. Es beinhaltet eine detaillierte

Abbildung von Energiebereitstellungs- und Energieverbrauchstechnologien, so dass

zukünftige Investitionen abgeschätzt werden können. Zudem bietet das Modell eine

ganzheitliche Bilanzierung von Primär-, Sekundär-, End- und

Nutzenergieverbräuchen für die gesamte Schweiz.

Die Analyse verdeutlicht, dass die 2000-Watt Gesellschaft nur als ein Langzeitziel

gesehen werden sollte. Im Jahr 2000 lag der Primärenergieverbrauch bei ca. 5000

Watt pro Person mit einem resultierenden energiebezogenen CO2-Ausstoss von 44.4

Mt. Unabhängig vom Ölpreis ist für alle untersuchten Szenarien eine

Verbrauchssenkung auf 3500 Watt möglich. Allerdings vermögen selbst starke

Primärenergieabsenkungen den CO2-Ausstoss nur um maximal 5 % pro Dekade zu

senken. Für stärkere CO2-Minderungsziele müssen diese explizit vorgegeben

werden. Wenn ausschliesslich CO2-Minderung als Ziel vorgegeben wird, senkt sich

der Primärenergieverbrauch, abhängig vom erwarteten Ölpreis im Jahr 2050,

lediglich auf 4900 bis 4500 Watt pro Person. Die Verfolgung von strikten CO2-Zielen

allein führt nicht zu der Erreichung des Ziels einer 2000-Watt Gesellschaft.

Die grössten Veränderungen in den untersuchten Szenarien betreffen sowohl

Energieumwandlungs- als auch Nutzenergietechnologien. In der Zukunft wird

xvi

Elektrizität eine immer wichtigere Rolle einnehmen. Die Produktion von Elektrizität

wird sich vom heutigen Niveau von ca. 57 TWh auf mindestens 70 – 85 TWh

steigern. Haushaltssektor und Fahrzeugflotte bedürfen einer vollständigen

Erneuerung, falls Energieverbrauch und CO2-Emissionen merklich gesenkt werden

sollen. Weiterhin sind die Reduzierung des Wärmebedarfs und der vermehrte

Einsatz von Wärmepumpen nötig. Auch die Nutzung von Erdgas- and

Wasserstoffautos wird in der Zukunft essentiell sein.

Jede umfassende Änderung des Energiesystems ist verbunden mit Kosten. Dazu

zählt auch eine schrittweise Annäherung an eine 2000-Watt Gesellschaft bis 2050.

Bei einem Ölpreis von 75 US$2000/bbl in 2050 betragen die Kosten ca. 20 Milliarden

US$2000 (~33 Milliarden CHF2000) um eine 3500-Watt Gesellschaft zu erzielen. Die

Kosten für ein Kyoto-für-immer Ziel (5 % CO2-Minderung pro Dekade) betragen im

Vergleich dazu nur ca. 15 Milliarden US$2000 (~25 Milliarden CHF2000), und sind damit

um 5 Milliarden US$2000 (~8 Milliarden CHF2000) geringer. Falls das übergreifende Ziel

ist, die CO2-Emissionen um 10 % pro Dekade zu senken und zudem eine 3500-Watt

Gesellschaft zu erreichen, liegen die Extrakosten bei ca. 40 Milliarden US$2000 (~67

Milliarden CHF2000), trotz potenzieller Technologie- und Kostensynergien. Somit ist

das Ziel der 3500-Watt Gesellschaft fragwürdig, falls das Hauptargument der

Primärenergiereduktion die Minimierung der CO2-Emission sein sollte.

Wenn Energieeffizienzmassenahmen mit dem alleinigem Ziel verbunden sind, die

Primärenergie zu senken, kommen wahrscheinlich wünschenswerte

Klimaschutzziele zu kurz. Moderate Importe von fossilen Energieträgern und die

verstärkte Nutzung von erneuerbaren Energien unterstützen CO2-Minderungsziele

erheblich. Obwohl die Studie nur potenzielle kosteneffektive Wege aufzeigt, ohne

nötige Anreize für diese Wege zu erörtern, wird dennoch ein Sachverhalt deutlich:

die Umwandlung des existierenden Energiesystems ist mit grossen

Herausforderungen verbunden. Zielgerichtete Umwandlungen werden nicht von

alleine passieren. Die Schweiz braucht daher genau diese zielgerichteten

Massnahmen ausgehend von Entscheidungsträgern, so dass die Bevölkerung Ihr

(Kauf-)verhalten ändert und in effizientere und saubere Technologien investiert. Je

früher Massnahmen in Angriff genommen werden, umso nachhaltiger werden die

Ergebnisse sein.

Stichwörter: 2000-Watt Gesellschaft, MARKAL, Schweiz, Energieökonomie

Introduction 1

1 Introduction

1.1 Motivation

In the last 50 years, an increasing demand for energy has boosted the consumption

especially of oil, natural gas and electricity drastically.[1] Besides all economical

benefits due to this high energy consumption, it also entailed several negative

aspects. Today, Switzerland is strongly dependent on imported fuels, which are

essential for today’s lifestyle. Many of those fuels are extracted in politically instable

countries e.g. Iran, Iraq or Saudi Arabia. Looking at the proved oil reserves, by far

most of them are located in Middle East countries.[2] Political tension could increase

and the question “who is eligible to use these resources” could probably be raised.

In 2002, Switzerland ratified the Kyoto protocol and committed to reduce CO2

emissions by 10 % of the 1990 levels by 2010.[3] Although the Swiss electricity

sector is basically CO2 free at the moment, other end-use sectors such as the

residential and transportation sectors emit significant amounts of CO2. Additionally,

due to probable strong demand increase of electricity, Switzerland is heading

towards an electricity gap around 2020.[4] If investments in fossil based electricity

plants cover this gap, CO2 is likely to increase further. If no measures are taken,

fulfilling the Kyoto and additional CO2 reduction targets will prove unlikely. The recent

IPCC report on climate change impacts, adaptation and vulnerability attracts major

international attention.[5] The report states: “Negative impacts [for Europe] will

include increased risk of inland flash floods, and more frequent coastal flooding and

increased erosion ... mountainous areas will face glacier retreat, reduced snow cover

and winter tourism, and extensive species losses.” The effect for Switzerland could

be dramatic if nothing will be done.[6]

Besides possible political tension and climate-change issues, the main question of a

globally fair-balanced energy consumption arises. Switzerland and to a large extend

the whole western world, currently uses much more energy than the world average.

On the one hand, the USA consume 12000 Watts per capita, Western-Europe 6000

Watts per capita and Switzerland still 5000 Watts per capita. On the other hand, in

Africa and in some Asian countries the PE consumption is less than 650 Watts per

capita.[7] Overall, 2000 Watts is the average world-wide energy consumption.

Therefore, many people claim that a 2000-Watt society should be seen as the long-

term goal to achieve a fair and sustainable development.[8]

Introduction 2

Controversial disputes will be ongoing. The focus could be on reducing energy

consumption by increasing the overall energy efficiency. The focus could also be on

lowering CO2 emissions by investing into renewable-energy technologies and

reducing the fossil import decency at the same time. It could also be on a

combination of targets. However, one fact is clear: Concrete measures have to be

taken if Switzerland wants to contribute to a clean and ecologically sustainable

environment. The challenge is to combine measures with a financially-flourishing

economy. Additional costs to undertake these measures need to be discussed

openly.

1.2 Scope of the analysis

This dissertation primarily aims at evaluating intermediate steps towards the 2000-

Watt society in Switzerland. The analysis quantifies possible reductions of primary-

energy per capita (PEC) use until 2050 and estimates the costs of such reduction

targets. Numerous energy balances and technological outlooks are documented:

• Primary energy per capita balances

• Final energy consumption balances by fuel and sector

• Residential heating technology projections

• Passenger car projections

• Electrical power station projections

• CO2 emissions projections

• Additional total system costs

Comprehensive sensitivity analyses has been performed to provide a full picture and

to test the robustness of the obtained results. The tested sensitivities comprise:

• Crude oil prices of 50 to 125 US$2000/bbl in the year 2050

• CO2 emission reduction targets of 5 and 10 % per decade, starting from the

Swiss-Kyoto target in 2010

• Discount rates of 3 and 5 %

• The influence of fuel-cell prices and stack sizes on hydrogen cars

• The influence of renewable energy-conversion equivalents on the production of

electricity

Introduction 3

• Comparison of the results to an analysis with an elastic demand responses

• Influence of oil prices and subsidies on the production of synthetic natural gas

(bio-SNG) from wood in a methanation plant

This dissertation conducts the first fully-integrated energy-system analysis (see

chapter 2), linking all Swiss energy sectors (energy production and energy-demand

sectors) in one modelling framework. Using this framework, the author analyses

various PEC reduction targets (including a combination of CO2 targets), derives all

energy and emissions balances and calculates the additional costs necessary to

change the structure and composition of the Swiss energy system.

1.3 Methodology

The questions surrounding the 2000-Watt society were addressed using a cost-

optimization modelling framework. A MARKet ALlocation (MARKAL) model provides

this framework. It represents a bottom-up energy-systems model that provides a

detailed representation of energy supply and end-use technologies (see chapter 3).

The family of MARKAL models has been developed by the Energy Technology

Systems Analysis Programme (ETSAP) that was established as an Implementing

Agreement of the International Energy Agency (IEA).[9] It is well documented and

described by the following publications: [10-12]. MARKAL models have been applied

for several national and multi-national case studies.[13,14] The original version of the

Swiss MARKAL model (SMM) has first been developed as a joint effort between

Energy Economics Group (EEG) at the Paul Scherrer Institute (PSI) and the

University of Geneva. Afterwards a number of improvements were implemented at

PSI. SMM has a time horizon of 50 years (from 2000 until 2050) with 5-year time

steps.

Due to the complexity of the task, the analysis was carried out step wise:

Step 1: Debugging and year-2000 calibration

The model was debugged, which included eliminating infeasibilities, linking

disconnected energy flows, removing non-existing energy flows and technologies,

etc. Primary and final-energy balances were recalibrated to official year-2000

statistics. The year 2000 is the base year of SMM (the starting year of the modelling

Introduction 4

framework). The year 2005, the second year of the modelling time horizon, has also

been calibrated to official statistics where and so far it was possible.

Step 2: General assumptions

General model assumptions were checked and overhauled where necessary. The

main assumptions include amongst others: Discount rates, potentials of energy

carriers, fuel and electricity imports and exports, population, GDP.

Step 3: Implementation of new biomass technologies

New biomass technologies were implemented into the modelling framework. As a

result, the assessment on the production of synthetic natural gas (bio-SNG) from

wood in a methanation plant was conducted.

Step 4: Renewal of the transportation and residential sector

The transportation and residential sectors were completely overhauled. In the first

phase two stand-alone models were developed before embedding them into the

SMM framework. The residential sector also includes demand reductions due to

energy-saving options (i.e. improved insulation of houses). The energy-saving

options were implemented in the model based on marginal-cost curves.

Step 5: Improved result evaluation

A modelling framework has been developed in VEDA and MATLAB to guarantee a

faster and more precise result evaluation.

Step 6: 2000-Watt society Analysis

The 2000-Watt society has been evaluated as a full-scale energy-system analysis.

1.4 Structure of the thesis

The document has been organised as follows. At first we define the objective of the

2000-Watt society and present a literature overview, before providing technical

background information. Afterwards we present all results of the analyses, and

summarize conclusions.

Introduction 5

Chapter 2: The 2000-Watt society

This chapter presents the definition and goals of the 2000-Watt society and explains

the importance of the concept. After providing a literature review, the chapter rounds

off by elaborating the 2000-Watt society from a today’s perspective.

Chapter 3: Defining the baseline

This chapter defines and elaborates the assumption of the “business-as-usual” or

baseline scenario. Additionally, it explains in detail how the transportation and

residential sectors are modelled and how energy-saving options were implemented in

SMM. It also provides a detailed overview of all relevant energy balances and CO2

emissions.

Chapter 4: Evaluating intermediate steps towards the 2000-Watt society

This chapter illustrates the main results of the document. It explains the result of the

2000-Watt society analysis, suggests a future technology mix in the year 2050 and

illustrates corresponding costs. The chapter contains an extensive sensitivity analysis

on various oil prices and CO2 targets.

Chapter 5: Complementary analyses

This chapter analyzes additional scenarios not yet covered in chapter 4. It presents

sensitivity analyses on discount rates, fuel cell prices and renewable energy-

conversion equivalents and evaluates the results using an elastic demand approach.

In that sense, the chapter fulfils the purpose of testing the robustness of the results.

Additionally it depicts an analysis assessing the production of synthetic natural gas

(bio-SNG) from wood in a methanation plant. The results of this analysis are

published in the journal ENERGY.[15]

Chapter 6: Conclusions and recommendations

This chapter draws conclusions based on all results evaluated within the scope of the

analysis and gives recommendations for the future development of the Swiss energy

system.

The 2000-Watt society 6

2 The 2000-Watt society

2.1 Description of the 2000-Watt society

In 1960, Switzerland was a 2000-Watt society. Today, more than four decades later,

the consumption has increased drastically. Due to all ecological and possible

economical (i.e. energy security) problems associated with a continuing increase of

energy consumption, important questions arise such as: What is a sustainable

energy consumption? How much energy should the developed world consume and

how much should developing countries consume to achieve an ecologically and

economically sustainable environment? One idea is to keep the total world wide

average energy consumption constant by achieving a (strong) economic

development at the same time. 2000 Watts is the average world-wide energy

consumption.[16]

The vision of a 2000-Watt society aims at consuming not more than 2000 Watts per

capita of primary energy (PE). In physics Watt is the unit of power and corresponds

to Joules (the SI unit1 of energy) per second. Therefore, the 2000 Watts target can

also be converted into an annual-energy consumption target or a consumption of

energy in a specific year. Assuming 365.25 days per year (including the leap year),

2000 Watts corresponds to 63.1 GJ per capita and year. What are the implications of

2000 Watts from a Swiss perspective? Given a population of 7.2 million for

Switzerland [18] and 366 days in the year 2000, 2000 Watts corresponded to 456 PJ

(per year) of PE. The Swiss Federal Office of Energy (SOFE) states a PE

consumption of 1132 PJ [1] (around 5000 Watts) in 2000. Therefore, for Switzerland

a 2000-Watt society implies to reduce the PE consumption by a factor of 2.5.

Figure 1 illustrates a possible pathway towards the 2000-Watt society in Switzerland

(the figure fulfils just an illustrative purpose).[7] The x-axis shows the time scale and

the y-axis the PE consumption per capita. In 2000, about 3000 Watts per capita

originate from fossil energy sources and 2000 Watts per capita from hydro power and

other renewable resources as well as nuclear fuels. From the middle of the last

century until now a large increase in consumption was typical for Switzerland,

comparable to the consumption of all developed countries. In the long-term the

present consumption might be seen as a peaking consumption. The vision is that due

1 International System of Units (SI is addreviated from the French Système international d'unités).[17]


to technological energy-efficiency improvements and fuel switching, the PE

consumption and especially its fossil share reduces significantly.

Figure 1: A possible development towards the 2000-Watt society.[7]

2.2 Literature review

This section presents overview of the most important literature about the 2000-Watt

society and closely related issues. Generally the present literature can be divided into

technical-feasibility studies and political scenario outlooks.

In 1985, Goldemberg et al. published a paper claiming that further living-standard

improvements are possible without increasing the per-capita use of energy above

present levels.[19] Having a focus on developing countries, they argued that for a PE

consumption of 1000 to 1200 Watts per capita, the “physical quality of life” could

reach the quality of industrialized countries if high-quality energy carriers and cost-

opportunities of more efficient technologies would be exploited. Further increases

would accomplish only marginal improvements of the quality. Compared to the

general assumption that energy consumption is the prerequisite for economic and

social development, Goldemberg opened ground for a highly controversial debated

issue. In 1994 and 1995, Goldemberg and Johansson also published reports about

“Energy as an Instrument for Socio-Economic Development” investigating “Energy

Needs for Sustainable Human Development”. They indicated that the vision of a


2000-Watt per capita society is likely to be technically (and eventually economically)

feasible.[20,21]

In 1997, von Weizsäcker et al. developed the formula „Factor 4“ as a new direction

for technological progress with the aim to double prosperity and to halve the resource

consumption in Germany.[22] Thereby, the efficient use of resources is the most

important instrument to achieve a sustainable development. This efficient use could

also be profitable to society. The book contains a variety of examples on how to

revolutionize productivity in the use of energy. It gives details how markets and taxes

can be organized to remove perverse incentives and to reward efficiency. The

benefits could be enormous.

A first onset to quantify possible PE scenarios in Switzerland was done by Kesselring

and Winter in 1994 taking up the term “2000-Watt society”.[23] They developed a first

technical-feasibility study with means of an energy-efficient transmission, minimizing

non-renewable and maximizing renewable energy sources. In 1998, the ETH-Rat2

postulated the idea of the 2000-Watt society emphasizing that such a society could

be achieved by the middle of the 21st century in Switzerland.[24] This was the starting

point for a number of analyses with a Swiss focus. The major analyses are briefly

described in the following paragraphs.

In 1999, the Swiss Academy of Engineering Science (SATW) analysed the possibility

of reducing the fossil energy consumption by 50 % compared to 1990 levels.[25] The

academy concluded that to reduce the consumption by 40 % until 2020 utilizing

energy-efficiency improvements is feasible. The reduction by 50 % would be possible

during the second half of the 21st century. In 2001, Spreng and Semadeni highlighted

the ecological and social aspects of a 2000-Watt society and defined the energy-

consumption per capita to be an indicator of sustainability.[26,27]

In 2002 and 2004 Jochem published two reports examining the question whether a

reduction of the per capita energy demand in Europe by two thirds is technically

feasible within 50 years, still achieving additional economic growth.[28,29] Enormous

efforts in R&D and a total turnover of the existing capital stock would be needed.

Technological progress and investments in low-energy houses, transportation and

2 The ETH Board is the strategic unit elected by the Swiss Federal Council to manage the ETH domain. It defines the domain's strategic direction and allocates the funding provided by the Swiss Confederation to the six institutions. The Swiss Federal Institutes of Technology Zurich and Lausanne (ETHZ and EPFL), The Paul Scherrer Insitute (PSI), the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), the Swiss Federal Laboratries for Materials Testing and Research (EMPA) and Swiss Federal Institute of Aquatic Science and Technology (Eawag) belong the the ETH domain.


power systems and industrial processes seem to be of major importance. In 2004,

other interesting studies were published in the context of a 2000-Watt society.

Marechal et al. [30] scrutinized “Energy in the Perspectives of a Sustainable

Development”, SATW [31] gave an outlook on renewable energy and EMPA on

reduction potentials of dwelling houses.[32]

In 2005, two important reports were published. In the energy-research strategy report

from Boulouchos et al., the authors acknowledged the 2000-Watt society as a

benchmark for sustainability. However, facing climate change, a per capita CO2

emission-reduction target would be more meaningful.[33] Koschenz and Pfeiffer

analysed the reduction potential in the residential sector in detail.[34] The authors

distinguish between realistic, ambitious and maximum-possible reductions in the

residential sector. While the total consumption by 2050 could be reduced by a factor

of 1.8 (44 %), 2.2 (55 %) and 5.1 (80%), respectively, the fossil consumption could

follow further reductions by a factor of 2.4 (85 %), 4.5 (78 %) and 14 (93 %),

respectively. Remarkably, neither Boulouchos et al. nor Koschenz and Pfeiffer

proposed specifically the year 2050 as the time horizon for the 2000-Watt society and

therefore support less ambitious targets than Jochem.

In the ETH annual report 2005 the 2000-Watt society is described as follows:

“Sustainability is the strategic target of energy research, as defined in the article on

energy in the Swiss Constitution. The associated vision of a 2000-Watt society

symbolizes the aspiration of achieving economic growth as planned, while using

distinctly less primary energy and clearly reducing CO2 emissions.”[35] The ETH-Rat

hopes that “the slogan of a 2000-Watt society ... will become engraved in people’s

minds and win them over to the long-term goal of reducing per capita energy

consumption to one third of today’s level, without lowering the standard of living.” In

this report a particular target date when the 2000-Watt society should be achieved is

not specified.

Of special importance is the Federal Energy Research Commission (CORE)3

roadmap from Bürer and Cremer. The report is a contribution to identifying promising

technologies in order to achieve the four objectives formulated by the Roadmaps

3 The Federal Energy Research Commission (CORE) acts as consultative body for the Federal Council and the Department of the Environment, Transport, Energy and Communications (DETEC). It defines the federal energy research concept, reviews and supports Swiss energy research programmes, comments on other energy research activities by the federal government and provides information concerning findings and developments in the area of energy research.[36]


Working Group4 in the context of the 2000-Watt society. It aims at supporting priority

setting in energy-research programmes and defines various possible futures for the

Swiss energy supply and demand by 2050.[37,38]

In 2006, additional relevant studies have been published. Most of them focused on

the residential sector. Worth mentioning are the dissertation from Kost about “Long-

term energy consumption and CO2 reduction potential in the Swiss residential sector”

[39] and the “Guidepost towards the 2000-Watt society” from Ellipson.[40] Kost

published his findings together with Siller and Imboden.[41] They conclude that

ambitious targets are necessary to reach the 2000-Watt society by 2050. In the

residential sector it is of foremost importance to reduce the specific heat demand of

existing buildings and to substitute heating and hot water systems by less carbon

intensive ones. Nevertheless, they argue that there might be more technical and

economical flexibilities than the 2000-Watt society if the target is to stabilize global

warming, due to greenhouse gas (GHG) emissions, at 2°C above pre-industrial

temperatures.

The question remains: What is the recommended approach of the Swiss Federal

Offices? The Swiss Federal Office of Energy (SFOE) has been publishing energy

perspectives in collaboration with external experts ever since the mid-1970s. Thereby

the aim has been to list options for planning a long-term and sustainable energy

policy that meets the principal requirements of supply security, protection of the

environment, economic viability and social acceptance.[42] In 2004, work has been

commenced on the preparation of so-called Energy Perspectives up to 2035.

Detailed results were published in a Management Summary at the end of February

2007.[43] Several accompanying documents to the final report (Scenarios I to IV,

economic impacts, analysis and evaluation of electricity supply and digressions) will

be published in the course of spring 2007. In particular, Scenario IV “Towards a

2000-Watt society” aims at reducing the PE consumption and strives for a reduction

of CO2 emission by half.[8] The results will be a basis for political debate on the

nature and content of Switzerland’s future energy and climate policies.[42]

4 The formulated objectives are a) no use of fossil fuels for heating requirements in the building sector b) a reduction of the energy consumption in the building sector by half c) an increase of the share of biomass in the energy supply while using its full ecological potential d) a reduction of the vehicle fleet’s average fossil fuel consumption down to 3 litres per 100 km.[37]


2.3 The 2000-Watt society from today’s perspective

From today’s perspective, it is still uncertain until when the vision of the 2000-Watt

society should be reached in Switzerland. However, it becomes more likely that the

formulation of the 2000-Watt society will include a combination of other targets. The

target of a 2000-Watt society alone probably comes too short when talking about

climate-policy issues because it does not distinguish between fossil and renewable

resources. In March 2007, the SFOE published the Swiss Federal Energy Research

Master Plan for the years 2008 to 2011.[44] This Master Plan, which could be seen

as the most prominent but non-binding energy plan, strives for the 2000-Watt society

as a prospective target in the second half of this century. Beside the target 2000

Watts, the plan also aims at the reduction of CO2 emission to an equivalent 1 ton per

person and year, similarly to the latest Energy Perspectives report (synthesis report

[45]) published in January 2007.

In the context of the 2000 Watts debate, one important issue was missing and is

addressed now. What are the additional costs to the society? Furthermore, all studies

published before are energy-sector specific or a combination of energy-sector

specific studies. This dissertation conducts a fully-integrated energy-system analysis

for the first time. Thereby, the author links all energy sectors (energy-production and

energy-demand sectors) using energy carriers (energy flows) in one modelling

framework. The interlinked energy sectors depict the energy system. Using this

framework, the author calculates concrete targets (including a combination of CO2

targets) for the year 2050 and derives the additional costs necessary to change to

structure and composition of the Swiss energy system. This way, the dissertation

enriches the existing literature on the 2000-Watt society.

2.4 Some energy definitions

For information purposes, energy (stored in energy carriers) can be classified into

different categories. The main categories are primary energy, final energy and useful

energy and are defined in [46].

Energy: Energy can be defined as the ability of a physical system to do work. Energy

can be stored in a system, transferred from one into another system or transformed

from one into another form. Energy cannot be created and energy cannot be

destroyed. The standard energy unit is Joule [J].


Energy carrier: A substance is considered an energy carrier if it stores energy that

can be used directly or after several conversion steps. For instance the energy

carrier coal can be burnt and the released heat transformed into electricity, which is

used in electrical devices.

Primary energy: The energy content of an energy carrier, which has not been

transformed in any way, for instance the energy content of crude oil in the ground

before any processing is done.

Final energy: The energy content an end-user obtains minus the non-energetic use,

the conversion losses and the own use in the conversion sector is defined as final

energy. In other words, it is the energy before the last transformation to its end use,

for instance the electricity needed to heat a room.

Useful energy: It is the energy an end-user needs for a specific purpose, for

instance the heat in a room or the lighting demand. Thus, it is the final energy minus

the transformation losses of end-use devices. Useful energy is sometimes also called

energy service.

Defining the baseline 13

3 Defining the baseline

3.1 Structure and main assumptions of the Swiss-MARKAL model

(SMM)

This dissertation analyzes the Swiss energy-system for the 2000-Watt society using

the Swiss-MARKAL model (SMM). SMM is a bottom-up energy-systems model that

provides a detailed representation of energy supply and end-use technologies. In this

section we describe the structure of the Swiss energy-system as it is modelled in

SMM and elaborate the main assumption needed to understand the model results.

Thereby, a special emphasis is put on the residential and transportation sector.

Oil

Natural Gas

Biomass

Other Renewables

Uranium

Coal

Refinery

Power Plants

Hydrogen Production

Heat Plants

Fischer-Tropsch

T&DCompressed Nat. Gas

Nat. GasBiomass

Residential(heating, lighting

cooking, appliances, etc)

Commercial/Services(heating, lighting,

appliances, etc)

IndustrialSector

Nat. Gas

Biomass

T&D

T&D

T&D

T&D

T&D

T&D

Transport(Cars, trucks,

railways, aircraft,etc)

Methanation,etc

T&D

AgricultureSector

Hydro

T&D

Figure 2: A simplified version of the Reference Energy System (RES) used in the energy-system Swiss-MARKAL

model. T&D is an abbreviation for transmission and distribution.

The backbone of the MARKAL modelling approach is the so-called Reference

Energy System (RES). The RES represents currently available and possible future

energy technologies and energy carriers. From the RES, the optimization model

chooses the least-cost energy-system, representing energy technologies and flows

for a given time horizon and given end-use energy demands. Figure 2 presents a

simplified version of the RES used in the SMM model. It illustrates energy flows in

Switzerland from production to the end-uses. Five main end-use sectors have been


considered, namely agriculture, commercial, industrial, residential and transportation.

All sectors are partitioned into sub-categories representing specific uses. The specific

uses are for example heating, domestic appliances and transportation modes. For

the purpose of simplicity, only the most relevant technologies and flows represented

in the model are included in Figure 2.

In following paragraphs we describe the main model assumptions. In this analysis, a

time horizon of 50 years (from 2000 until 2050) with five-year time steps has been

chosen. For the baseline scenario a discount rate of 3 % is used in all calculations (a

discount-rate sensitivity analysis is conducted in an additional section). The currency

units used in this report are US dollars of the year 2000 [US$2000]. Costs and

potential of resources as well as costs, potential and technical characteristics of the

technologies are time dependent. Overall, the base year of the model has been

calibrated to officially published Swiss energy statistics [1,47,48] and to IEA statistics

[49] of the year 2000, respectively. The statistics are choosen depending on the

quality and the level of detail of the obtained data.

The population projection used in our scenarios correspond to the scenario ‘A-Trend’

reported by [18]. It is based on a continuation of recent historical trends and middle

values for fertility rates, immigration flows and life expectancy. In ‘A-Trend’ scenario,

the population of Switzerland increases from about 7.2 million inhabitants in 2000 to

about 7.4 million inhabitants in 2030. Afterwards, the population experiences a slight

decline reaching about 7.1 million inhabitants in 2050. The GDP projection used here

corresponds to the scenario reported by [50]. The GDP is assumed to increase by

nearly 50 % from the year 2000 to the year 2050.

Another important assumption concerns the prices of oil and natural gas resources

for which moderate increments are assumed in the first half of the 21st century in this

scenario (see Table 1). The crude oil price is assumed to constantly increase from

4.6 US$2000/GJ (equivalent to 29US$2000/bbl) in the year 2000 to 8 US$2000/GJ

(equivalent to 50 US$2000/bbl) in the year 20505. Natural gas is assumed to be linked

to the crude oil price. Hence the price increases from 3.3 US$2000/GJ in the year 2000

to 5.7 US$2000/GJ in the year 20506. Given the large uncertainty that surrounds the

development of the price of fossil energy resources, a sensitivity analysis needs to be

5 In the model crude oil is refined among others to diesel, gasoline, kerosene, and heavy fuel oil. To calculate the end-user price for crude oil products additional variable cost for the operation of the refinery of 2.3 US$2000/GJ and the distribution costs for diesel and gasoline of 1.23 US$2000/GJ have to be added. 6 The transmission cost of natural gas are assumed to be 1.00 US$2000/GJ.


conducted for most results. Moreover, two important assumptions relate to the

distribution of costs and taxes. The model includes distribution costs for all fossil

recourses. However, the model does not contain taxes for any fuel use. The

implication of this assumption is explained in chapter section 5.5 where subsidies are

used as a policy measure.

Table 1: Prices for fossil energy resources as assumed in this study. For a better understanding, the oil price is

given both in US$/GJ and in US$/bbl.

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Natural Gas (US$/GJ)

3.3 3.6 3.8 4.0 4.3 4.5 4.8 5.0 5.2 5.5 5.7

Crude Oil (US$/GJ)

4.6 5.0 5.3 5.6 6.0 6.3 6.7 7.0 7.3 7.7 8.0

Crude Oil (US$/bbl)

29 31 33 35 37 39 41 43 45 47 50

3.2 Renewable energy potential and nuclear energy

When it comes to the projection of the future energy consumption, it is of major

importance to define reliable renewable energy potentials. In 2005, the Paul Scherrer

Institute (PSI) published a report for the Swiss Federal Office of Energy (SFOE),

estimating cost and potentials of new renewable energies in Switzerland [51]. The

renewable energy supply options7 considered in the report were defined by SFOE

according to their future importance. The renewable technologies and their

corresponding potential investigated are: small hydro, wind energy, photovoltaics,

solar thermal and solar chemical generation, geothermal and wave power. Generally

speaking, the renewable potential in Switzerland is very large in comparison to the

energy demand. However, this is rather based on theoretical (maximum available

resources) than on technical and economical grounds. Therefore, in the following

paragraphs we provide estimations on the technical potential of renewable energy

sources.

Electricity generation from small hydro power poses an economical and ecological

interesting option. However, the questions about the maximum hydro-power potential

is complex to answer. They comprise issues such as the physical potential along a

river, hydro-power plants worthy to be upgraded, potential (but not yet built) power

stations, etc. Presently about 3400 GWh/yr (12.2 PJ) electricity is generated from

small hydro power stations (<10 MW). This could be raised to 5600 GWh/yr (20.2 PJ)

7 The options considered in the report refer to potential to produce electricity. However, especially the theoretical potential for biomass refers to the total potential, which can also be utilized by other non-electricity production options.


in the year 2050 for an average generation cost of about 10-25 Rp/kWh

(1 € = 155 Rp). The maximum technically realistic achievable potential for water

purification and wastewater plants is fairly small. Their additional potential is around

155 GWh/yr (0.6 PJ). In recent decades there have been many studies about the

total unused potentials of hydro power including large hydro power stations (>10

MW). The latest study was published by SFOE in 2004.[52] The study sees a total

potential for additional expansion of 7570 GWh/yr, or about 14 % of the total present

electricity production.

The current use of wind power is negligible in Switzerland, about 2.98 GWh/yr

(0.01 PJ) in 2000. However, various studies have shown that the realistic technical

potential from wind parks is around 1150 GWh/yr (4.1 PJ) by 2050, divided into 96

locations. Additionally individual turbines could produce 2850 GWh/yr (10.3 PJ).

Whereas present generation cost of wind power plants are between 12-15 Rp/kWh, a

cost reduction to 11.6-13.8 Rp/kWh may be expected by 2050. Compared to other

renewable energies wind power undergoes regular recurring objection based on

protection of landscape and nature claims.

The available wood potentials may be estimated in many ways, for example by

establishing the theoretical8 or ecological9 potentials. In this report we have used the

theoretical-potential approach corresponding to the ‘A’ category (natural-wood

assortments from forestry including hedges and biomass from fruit-growing10).[53]

Hence, in the year 2000 we assume the total wood potential to be in the range of 96

PJ/year, and rising to about 103 PJ/year by the end of the analysis timeframe 205011.

In order to better represent the real market conditions, following literature source [53],

we have assumed that the wood price is dependent on its availability. In SMM we

modelled three price categories ‘high price’, ‘medium price’ and ‘low price’ In the year

2000 the medium price for wood is 5.23 US$2000/GJ, the low and high price is

respecticely 10 % lower and higher. Therefore, an increasing demand for wood

consequently raises its price, as soon as the feedstock of e.g. low-priced wood is

exhausted. Low price and high price biomass make up 40 % of wood available (equal

8 The theoretical potential is defined in [53] as ‘based on wood grown in productive land surfaces and residues from secondary production and human consumption that be reutilized’. 9 The ecological potential is defined in [53] as ‘ecological net-production potential respectively the share of biomass that can be used for energetic treatment without material utilization’. 10 In [53] natural wood assortments from forestry, including hedges and biomass from fruit-growing, are described in the category ‘Waldholz, Feldgehölze, Hecken’. 11 [54] considers the total energetic biomass potential to be 180 PJ in Switzerland. Hence the potential we use in this report is a rather conservative assumption.


shares). The medium-priced wood is available for the remaining potentital of 60 % in

Switzerland.

In recent years the photovoltaic capacity has grown by 15.3 % per year. At the end of

2003, the total installed capacity was about 21 MW. However, in future times the

potential will be limited by the availability of roof-surfaces and the increased

construction times. Due to those two limitations, for the report we only assume the

technical available potential for very well suited roofs (quality factor > 90 %), which

adds up to a maximum of 13.7 TWh/yr (49.3 PJ).

Switzerland has a large potential for geothermal energy from deep hot rock.

However, to estimate the technical potential we need to reduce the uncertainties

concerning the quality of the geothermal resource and the cost of drilling and the cost

of generating electricity and heat. SFOE is currently developing a “Deep Heat Mining”

in Basel with a thermal capacity of 20 MW, an annual electricity production of

20 GWh and an annual heat production of 80 GWh. A similar project is planned for

Geneva but exact potential estimations do not exist so far. Therefore, in the course of

this study we assume a conservative (and quite uncertain) potential of about

1388 GWh/a or about 5 PJ in 2050. However, possible earthquakes like in Basel may

pose certain threads to geothermal projects in Switzerland.[55]

Other important elements of our scenarios are related to the future role of nuclear

power plants within the Swiss energy system and electricity imports. In this scenario,

we have assumed that the electricity generation from nuclear power plants remains

at maximum at its year-2000 levels for the entire time horizon. The generation of

electricity could be lower but can not be higher. This presupposes a possible

replacement of nuclear plants scheduled to be decommissioned in the next decades

but it does not assume the introduction of any new nuclear power plants. It must be

recognized, however, that the future role of nuclear energy in Switzerland will

depend, among other factors, on addressing the issues of higher nuclear safety,

disposal of nuclear waste, proliferation resistance of fuel and public acceptance and

the related political decisions on these topics. As for the imports and exports of

electricity, we have assumed that from the year 2010 onwards exports will become

equal to imports. Under this assumption, Switzerland remains independent from

neighbouring EU countries in terms of its electricity supply in the long-term.


3.3 Energy and emission balances of the baseline scenario

In order to give an adequate context to our analysis we describe the main

characteristics of the baseline scenario in this section. Scenarios in general can be

refered to as alternative images of how the future might unfold. They are an

appropriate tool to analyze how driving forces may influence future outcomes and to

assess the associated uncertainties.[56] The baseline scenario portrayed here

depicts future trends in the energy system of Switzerland without any radical political,

technical or social change. In this sense, it represents a plausible middle-of-the-road

development of the Swiss energy system. In addition to the baseline scenario, we

analyse complementary scenarios in the next chapters. In these complementary

scenarios we assign different values for key variables such as oil and gas import

prices and introduce CO2 or primary energy constraints, among others. On the one

hand, they help examining the impact of uncertainties in baseline assumptions and,

one the other hand, they allow conducting what-if analysis. Hence, they give

assistance to a decision-making process. In the following paragraphs we give insight

to the trends in primary, final and electric-energy consumption and the CO2

emissions in the baseline scenario.

3.3.1 Primary-energy balances

Figure 3 represents the primary energy consumption in Switzerland for the baseline

scenario up to the year 2050. In the figure, the efficiency of a hydro power plant is

assumed to be 80 % and the efficiency of a nuclear power plant is assumed to

remain constant at 33 %. These values correspond to those used by the Swiss

energy statistics for the computation of the primary-energy equivalent of the

electricity generation of these two technologies.[1] Although electricity is not a

primary-energy source, the graph includes the net imports (i.e. imports minus

exports) of electricity to Switzerland to account for the completeness.


-200

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2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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ma

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rgy

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um

pti

on

[P

J]

ElectricityRenewablesHydro PowerNuclear PowerGasOilCoal

Energy carriers:

Figure 3: Primary-energy consumption in the baseline scenario for the period 2000 to 2050.

In this baseline scenario, primary energy consumption remains relatively stable at

around 1200 PJ over the time horizon, slightly decreasing towards the year 2050. Oil

continues to hold an important share of the Swiss primary energy mix but its

consumption experiences a sizeable decline due to the increasing oil price and

efficiency improvements in the transportation sector. Natural gas, on the other hand,

experiences a significant increase. The contribution of nuclear energy and hydro

power remain approximately constant. Other renewable energy sources play only a

modest role in this scenario.

Figure 4 shows the primary energy per capita consumption. Literature values are

presented for the years 1910 until 2000 and baseline projections for the years 2000

until 2050. Until the year 1950, the per capita consumption was very stable at around

1000 W/cap. From 1950 until 1985, we can see a strong increase in the per capita

consumption to nearly 4700 W/cap. After the year 1985, a stabilisation of the strong

increase is noticeable; the per capita consumption only increases moderately

thereafter. This trend is confirmed by the baseline projection of SMM. In the year

2050, we reach a per capita consumption of about 5300 W/cap for the baseline-

scenario projection.


0

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/Cap

ita]

Literature values Baseline projection

Figure 4: Primary-energy per capita consumption for the period 1910 to 2050. The figure shows literature

values [18,57,58] for the time period 1910 until 2000 and values of the baseline projection for the time period

2000 until 2050.

3.3.2 Final-energy balances

The final-energy consumption of the base year has been calibrated to officially

published Swiss energy statistics [1] and to IEA statistics [49] of the year 2000,

respectively, depending on the quality of the obtained data. Relevant statistics as

well as the model calibration for final-energy consumption of the year 2000 are

presented in the appendix 4.

Figure 5 and Figure 6 show the final-energy consumption by sectors and by energy

carriers for the baseline scenario.12 The total final-energy consumption increases

only marginally from about 885 PJ in 2000 to about 925 PJ in 2050. Oil products,

natural gas and electricity dominate the final-energy mix over the whole time horizon.

While natural gas and electricity increase in absolute terms, the overall consumption

of oil products reduces over time. The consumption of biomass and waste remains

stable over the time horizon. Other energy carriers play a minor role in the primary

energy mix. In terms of sectors, the largest consumer of final energy remains the

transportation sector. The share of this sector in the final-energy consumption of

12 Final energy is defined as the energy that is available to the consumer.


Switzerland amounts to approximately 32% in the year 2050. Overall the sector

consumption remains at constant levels in the baseline scenario.

0

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2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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al

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mp

tio

n [

PJ]

Other RenwablesWasteDistrict heatWoodCoalGasOil ProductsElectricity

Energy carriers:

Figure 5: Final-energy consumption by energy carriers in the baseline scenario for the period 2000 to 2050.

Note that in the figure Other Renewables refer to the use of solar energy, biogas and

ambient heat following [1]. Non-energy use covers use of other petroleum products

such as white spirit, paraffin waxes, lubricants, bitumen and other products. It also

includes the non-energy use of coal (excluding peat). These products are shown

separately in final consumption under the heading non-energy use. It is assumed that

the use of these products is exclusively non-energy use. Other non-specified

includes all fuel use not elsewhere specified (e.g. military fuel consumption with the

exception of transport fuels in international marine bunkers and consumption in the

above-designated categories for which separate figures have not been provided).

[59]


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PJ]

IndustryTransportationResidentialCommercialAgricultureNon-Energy UseOther non-specified

Sectors:

Figure 6: Final-energy consumption by sectors in the baseline scenario for the period 2000 to 2050.

3.3.3 Electricity production and consumption

Figure 7 presents the electricity generation mix under the baseline scenario. 13 Net

imports of electricity are included (negative values mean that Switzerland is exporting

electricity).14 With the assumptions made in this scenario, no major structural

changes in electricity generation take place during the first half of the 21st century.

Electricity generation grows gradually and remains largely CO2-free. Conventional

nuclear and hydro power plants provide the bulk share of production. Nuclear-based

electricity production remains at the year-2000 levels over the whole time horizon.15

This implies a replacement or life extension of the nuclear power plants expected to

be decommissioned in the coming decades. Hydroelectric generation, on the other

hand, experiences an increase, mainly due to the tapping of the available small hydro

potential.16 Natural gas-based cogeneration facilities and wind turbines make some

13 The category ‘Conventional Thermal and Others’ includes non-hydro electricity auto-production from the railways system and the industry.[60] Hydro-based auto-production from the railways system and the industry is included under the category “Hydro Power”.[60] 14 Our analysis assumes that in the long term net imports/exports of electricity are reduced to zero. 15 In this scenario, an upper bound on electricity generation from nuclear power has been imposed. At most, the electricity production levels of the year 2000 can be reached. 16 [51] estimates that the additional potential for small hydro power plants in Switzerland amounts to approximately 5.6 TWh/year.


inroads towards the end of the time horizon but they remain minor contributors to the

Swiss electricity generation mix.

-10

0

10

20

30

40

50

60

70

80

90

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Ele

ctr

icit

y P

rod

ucti

on

[T

Wh

/year]

Wind TurbinesBiomass CogenerationNatural Gas CogenerationConventional Thermal and OthersHydro PowerNuclear PowerNet Imports

Electricity production technologies:

Figure 7: Electricity production in the baseline scenario for the time period 2000 to 2050.

Figure 8 shows the correlation between electricity consumption and GDP for the time

period from 1980 to 2050, whereby the time period from 1980 to 2000 reflects

statistical values and the time period from 2000 to 2050 SMM values of the baseline

scenario. This correlation is based on the assumption that the energy demand is

equal to the GDP to the power of α . In a linearized form this can be expressed as

)ln()ln( GDPndEnergyDema ⋅= α or bxy +⋅= α . Thereby, α represents the gradient

of slope or the income elasticity of demand (for electricity). If α is 1 GPD is directly

proportional to the electricity consumption. If α greater than 1 the electricity demand

increases faster than GPD and if it is smaller the electricity demand increases slower.

The figure is divided into a left part, representing historic literature values, and a right

part, representing the baseline energy consumption (baseline projection) of

Switzerland. The historic as well as the projected GPD is taken from the Swiss

Federal Statistical Office.[61] Having some fluctuations for the α values for certain

time periods, overall the figure shows a relative constant slope. Despite an indicated

decline of the slope after the year 2040, the income elasticity of electricity demand is

around one. Note, that this fit is used as a qualitative trend assessment without

considering price effects and price elasticises with natural gas and oil.


y = 1.2326x - 10.651

y = 0.8847x - 6.2065

y = 0.9948x - 7.6192

y = 0.7938x - 5.0045

y = 1.2076x - 10.445y = 0.6141x - 2.6081

y = 0.3397x + 1.0283

4.8

4.9

5.0

5.1

5.2

5.3

5.4

5.5

5.6

12.5 12.6 12.7 12.8 12.9 13.0 13.1 13.2 13.3 13.4

1980-1990

1990-2000

2000-2010

2010-2020

2020-2030

2030-2040

2040-2050

ln (electricity demand)

ln (GDP)

Literature values Baseline projection

Literature values

Literature values

Baseline projection

Baseline projection

Baseline projection

Baseline projection

Baseline projection

Time periods:

Figure 8: Correlation between electricity consumption and GDP for the time period 1980 to 2050. The time

period 1980 to 2000 reflects literature values [57,58,61] and the time period 2000 to 2050 SMM values of the

baseline-scenario projection.

3.3.4 CO2 emissions

In this baseline scenario, the total energy-related CO2 emissions are reduced from

about 44.8 million tons of CO2 (Mt) in the year 2000 to 42.6 Mt of CO2 in the year

2050 (see Figure 9). This small reduction is mainly due to changes in the Swiss

energy system, triggered by the sustained increasing oil price signal. Note, however,

that the effects of the oil price alone do not lead to any substantial reduction in CO2

emissions. The emission shares of the various sectors stay relatively constant. The

transportation sector is by far the largest CO2 polluter, followed by the residential

sector. The one sector with increasing CO2 emissions is the electricity sector.

Because of the cap on nuclear energy, increasing demand for electricity is covered

by natural gas CHP plants. The Swiss CO2 law and the achievement of the Swiss

Kyoto targets have not been considered in this baseline scenario.


0

5

10

15

20

25

30

35

40

45

50

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

CO

2 E

mis

sio

n [

Mt] Transport

ResidentialIndustryCommercialAgricultureUpstreamElectricity

Sectors:

Figure 9: Energy-related CO2 emissions per sector in Switzerland for the period 2000 to 2050 in the baseline

scenario.

3.4 Description of the residential sector

The residential sector is a central end-use energy sector in Switzerland when it

comes to final-energy consumption and energy-saving potentials. With a final-energy

consumption of more than 230 PJ in the year 2000, the sector is the second largest

energy consumer after the transportation sector. The biggest challenge in the

residential sector is the long life-time of the building stock. Once a building has been

refurbished or built, it takes several decades before new investments in

refurbishment (e.g. advanced energy-saving insulation-measures or heating

systems) will possibly be made. Therefore, when it comes to reducing energy

consumption, it is most important to combine refurbishment actions with actions

directly related to energy-saving measures.

In total we distinguish 13 demand segments in the residential sector, see Table 2.

The most important segment in terms of energy consumption is ‘Residential Heating’

(RH). RH is a special category due to the complexity of energy saving potentials.

This is why we divided the segment into four separate demand segments: Single and

Multi Family Houses (SFH and MFH) for existing and new buildings. In the model we

refer to dwellings constructed before the year 2000 as existing buildings, and


dwellings constructed after the year 2000 as new buildings. For our modelling

exercise this differentiation provides a detailed representation of the RH sector.17

Table 2: Demand segments of the residential sector.

Description Abbreviation

Cooling RC1

Cloth Drying RCD

Cloth Washing RCW

Dish Washing RDW

Other Electric18

REA

Room-Heating Single-Family Houses (SFH) existing building RH1

Room-Heating Single-Family Houses (SFH) new building RH2

Room-Heating Multi-Family Houses (MFH) existing buildings RH3

Room-Heating Multi-Family Houses (MFH) new buildings RH4

Hot Water RHW

Cooking RK1

Lighting RL1

Refrigeration RRF

3.4.1 Base year calibration

Table 3 shows the final-energy consumption of each residential demand segment for

the year 2000 as it is modelled in SMM and compares it to International Energy

Agency (IEA) and the Swiss Overall Energy statistics (GEST)19. The model

calculates a total final-energy consumption of 232.1 PJ. According to IEA statistics

for the year 2000, 234.6 PJ of final energy was consumed in the residential sector of

Switzerland. This value is of the same magnitude as the consumption in GEST.

GEST state a final energy consumption of 230.6 PJ.20 Based on the total final-energy

consumption and consumption shares taken from [62] and [63], the final-energy

consumption of each demand segment is calculated.

Table 3: Final-energy consumption 2000 in [PJ] – split by demand segments and fuels.

Description Model Code

Coal Oil

Products Gas Biomass

Other Renewables

Electricity Heat Total

Cooling RC1 1.8 1.8

Cloth Drying RCD 1.4 1.4

Cloth Washing RCW 4.6 4.6

Dish Washing RDW 1.7 1.7

Other Electric REA 11.5 11.5

Heating SFH exiting RH1 0.2 50.5 15.1 3.8 1.5 7.7 78.8

17 In reality existing buildings represent a manifold building stock with various insulation qualities (building code). For instance, dwellings constructed 50 years ago have less thermal insulation compared to dwellings constructed 10 years ago. New buildings in 10 years time will also be constructed with improved insulation thicknesses depending on the investor’s willingness and possibilities to pay. 18 The demand segment Other Electric represents devices such as television sets, computers, stereos sets, etc. 19 GEST is the abbreviation for Schweizerische Gesamtenergiestatik (Swiss Overall Energy Statistics). 20 This corresponds to 240 PJ with adjustments for heating degree days.


buildings

Heating MFH existing buildings

RH3 0.2 56.9 17.1 4.3 1.7 4.3 4.3 88.9

Hot Water RHW 14.0 5.1 0.4 0.2 6.9 0.8 27.4

Cooking RK1 0.6 0.1 5.3 6.0

Lighting RL1 5.6 5.6

Refrigeration RRF 4.4 4.4

MARKAL Total 0.4 121.5 37.9 8.5 3.5 55.1 5.1 232.1

GEST Total 0.1 121.0 36.3 8.6 3.4 56.6 4.6 230.6

IEA Total 0.4 124.3 36.3 8.8 3.5 56.6 4.6 234.6

References: [1], [62], [49], [63]

As can be seen in the table, space heating (Heating) is the sub-sector with the by far

highest final-energy demand, consuming more than 70 % of the total final energy.

The second largest sector is hot water, followed by other electrical devices. Looking

at the fuel consumption, the residential sector is highly dependent on fossil fuels. Oil

and gas products nearly provide 70 % of the total final-energy consumed. Space

heating and hot water are the main consumers of fossil products, whereas all other

demand segments mainly consume electricity. Looking at the 2000-Watt society, the

main goal is to reduce the high dependency of oil and gas products and to install

energy-saving measures to reduce the space heating demand.

3.4.2 Future projection

In this section, we illustrate information important to understand the future energy

consumption of the residential sector. Special emphasis is put on the demand

segment Residential Heating (RH). In detail, the section describes the future

residential heating technologies, demand projections and the implementation of

energy saving options. Additionally the section focuses on other than RH demand

projections and provides a final-energy consumption overview.

3.4.2.1 Residential-heating technologies

Table 4 portrays all heating technologies optional in the model. We decided to

provide an as large variety of heating technologies as possible.

Table 4 shows the heating technologies available for every heating demand segment

(RH1 to RH4 – see Table 3). Note that district-heating technologies are limited to

MFH since their application to SFH in the Swiss context appears to be rather small. A

detailed technology description can be found in the appendix 1.


Table 4: Future heating technologies.

RH1 RH2 RH3 RH4

Biomass (Wood)21

� � � �

Oil � � � �

Natural Gas � � � �

Heat Pump – Sole � � � �

Oil Solar � � � �

Natural Gas Solar � � � �

Pellets � � � �

Heat Pump – Air � � � �

Pellets – Solar � � � �

Heat Pump – Water � � � �

District Heat � �

3.4.2.2 Demand projection of the residential-heating sector

As mentioned above, in SMM we distinguish 14 different demand segments. In this

section we focus on the four most important demand segments, the RH demands.

RH is separated into SFH and MFH as well as existing and new buildings. In the

model we refer to dwellings constructed before the year 2000 as existing buildings

and dwellings constructed after the year 2000 as new buildings. Assuming future

specific RH demands and Energy Reference Floor Areas (ERFA)22, the absolute

demand values for space heating can be projected using the general formula:

[ ] [ ] [ ]22// mMioERFAamMJDemandHeatingRoomSpecificaTJEnergyUsefulDemand ⋅==

A first estimation of ERFA was done by Wüest & Partner in the year 1994 [65] (see

[32]). In recent years this projection has been updated several times [32]. In order to

estimate ERFA projections several sources tried to link construction investments with

the economic situation and the population development [62,66]. Figure 10 shows the

latest ERFA projection including extrapolations by the author (PSI Projection). The

author’s projections were necessary because all literature references available only

provide ERFA values up to the year 2035, while SMM analyses future scenarios until

2050.

21 Biomass (wood) is a aggregation for Chemineés fireplaces and other stoves, such as tiled stove. Residential heating systems based on pellet firing are aggregated in a separate category. 22 ERFA is defined in SIA 380/1 as the sum of all overground and subsurface floor areas subject to heating and air-conditioning.[64]


0

100

200

300

400

500

600

700

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

[Mio

m2]

Prognos 2005 PSI Projection BFE 2002

Figure 10: ERFA comparison.

References: [62], [66], [67], [68], author’s assumptions

Existing buildings:

As described above, the model defines four RH demands for existing and new

buildings. In order to project the future ERFA for existing buildings, base year

demand splits of SFH and MFH, specific RH demands and demolition rates are

assumed. In the year 2000 we assume that 46 % of the total ERFA belongs to SFH

and 54 % to MFH (based on [69]), which results in 187 [Mio m2] ERFA for SFH and

222 [Mio m2] for MFH. To calculate the energy demand of existing buildings, the

ERFA of each house type (SFH and MFH) has to be multiplied with the specific RH

demand [MJ/m2]. [69] assumes a specific RH demand of 384 [MJ/m2] for SFH and of

364 [MJ/m2] for MFH in the year 2000. Taking these assumptions into account, we

calculate an energy demand of 72 [PJ/a] for SFH and of 80 [PJ/a] for MFH in 2000.

Furthermore, we assume that the specific RH demand of existing remains constant

over the whole time horizon in the reference scenario. The model is then able to

implement energetic improvements depending on the constrained scenarios. Hence,

energetic improvements of the annual energy consumption of each house are fully

covered by the energy-saving options described below. Due to the future demolition


rates, the demand decreases to 70 [PJ/a] and 74 [PJ/a] respectively until 2050, see

Figure 12. The splits and the demolition rates are assumed by [63] and [69]. The

demolition rates and the resulting ERFA for exiting buildings are both depicted in

Figure 11.

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

RH1 RH3 RH1 Projection RH3 Projection

Demolition Rate of Existing Buildings.

Reference: [69] and own calculations

150

160

170

180

190

200

210

220

230

240

250

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

[M

io m

2]

RH1 RH3

ERFA Existing Buildings.

Reference: [69] and own calculations

Figure 11: Demolition rate and ERFA existing buildings. 23

0

10

20

30

40

50

60

70

80

90

100

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

[PJ/a

]

RH1 RH3

Figure 12: Energy demand existing buildings SFH (RH1) and MFH (RH3).

23 RH1 refers to SFH and RH3 to MFH.


New buildings

To estimate demand projections for new buildings, we need to predict ERFA values

and specific RH demands for SFH and MFH new buildings. To calculate these values

a different approach is required than it is used for existing buildings. A subtraction of

the total ERFA (Figure 10) from the future ERFA for existing buildings (Figure 11)

provides the ERFA of new buildings. The result of this calculation is displayed in

Figure 13. For new buildings the demolition rate is very small, less than 1 % in 50

years. Hence, for simplification we assumed that all newly constructed buildings have

a life time of at least 50 years. Considering the time horizon of 50 years of SMM, the

error from this simplification is negligible.

0

20

40

60

80

100

120

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

[Mio

m2]

RH2 RH4

Figure 13: ERFA new buildings SFH (RH2) and MFH (RH4).

Several references are available, which describe the development of specific RH

demands [MJ/m2] of new buildings ([62], [67], [32], [64], [70] and [71]). Following [62]

with additional assumptions made by the author, we obtain average specific RH

demands for SFH and MFH (see Figure 14) built in the future. The average specific

RH demand in this figure relates to a newly constructed house at the period of time

indicated in the figure. The values do not relate to the specific vintaged demand of all

new buildings in a future period. The specific vintaged demand would refer to a


mixture of new buildings constructed prior to a certain period of time t-1 and the

newly constructed buildings at that period of time t.

0

50

100

150

200

250

300

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

[MJ/m

2a] RH2

RH2 ProjectionRH4RH4 Projection

Figure 14: Average specific room-heating demand of new buildings built in a future period of time.

References: [62], own assumptions

The energy demand of new buildings is calculated according to the following formula:

20502005)( 11 ≤≤∀+−⋅= −− tDMDERFAERFASDDMD ttttt

DMD: Demand of New Buildings

SD: Specific Room Heating Demand

ERFA: Energy Reference Floor Area

t: Time Period

Using this formula we estimate the room heating demand of new buildings, displayed

in Figure 15.


0

5

10

15

20

25

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

[PJ/a

]

RH2 RH4

Figure 15: Room-heating demand new buildings energy saving options.

3.4.2.3 Implementation of energy-saving measures

Marginal Conservation Cost curves for the Swiss RH sector were first developed by

Jakob and Jochem [67,72] and made available to PSI for this study. Marginal Costs

(MC) describe the additional prices for better sealed insulations and the unit of the

corresponding energy efficiency yield. In other words, MC relate the additional

annualized investment costs of an energy-efficiency measure (or a set of measures)

to the energy-demand reduction of this measure. [72] explains the MC of an energy-

saving measure using the formula below. For developing a cost curve, it is most

important to define a reference development because all additional investments and

their associated energy savings are based on this reference. For our analysis this

reference development corresponds to the specific RH demand described in the

previous chapter.

1,,

11

−

−−

−

−=

∆

∆≅=

nEnergynEnergy

nnnn

EnergyEnergy

EEDD

InvCostaInvCosta

D

CapCost

dD

dCapCostmc

)...1( Nn∀

mcEE : Marginal Cost of Energy Efficiency Conservations in Buildings

CapCost: Capital Cost of Energy Efficiency Conservations in Buildings

InvCost: Investment Cost of Energy Efficiency Conservations in Buildings


DEnergy: Energy Demand of a Building

n and n-1: Energy Demand Level of the Building considered

N: Maximum Number of Saving Measures Considered

a: Annuity Factor

For the implementation we distinguish between existing buildings (RH1 and RH3)

and new buildings (RH2 and RH4). For existing buildings we have assumed the

specific RH demand of the year 2000 to be constant for the whole model horizon and

included options to reduce this demand. In this case all conservation measures

introduced are completely dependent on the model optimization results. The specific

RH demand without reductions is called the reference specific RH demand. For new

buildings we have assumed a constant building-code improvement for the whole time

horizon (the energy efficiency of each house increase, therefore, the specific RH

demand decrease). Hence, we implement two specific MC curves for existing

buildings, one for SFH and another for MFH. For new buildings we additionally

implement MC curves for each time period analysed in the model.

Existing buildings

Before being able to implement the MC curves for SFH and MFH in the model, each

curve has to be calibrated to the starting year 2000. The basis for each existing

building MC curve calibration is four separate curves reflecting the year of

construction of existing buildings. We distinguish between houses being built before

1947 (type I), between 1947 and 1975 (type II), between 1975 and 1985 (type III) as

well as between 1986 and 2000 (type IV). Note that buildings constructed after 2000

are referred to as new buildings in the model.

Figure 16 depicts the reference MC curves for SFH and MFH. On the x-axis the

specific RH demand in [MJ/m2a] is portrayed and on the y-axis the MC in [CHF/kWh].

The graphs show that specific MC curves also include very low quality building

codes, which are not relevant for the base year 2000. Hence, the starting point of the

curve (conservation measures) had to be calibrated such that it corresponds to the

specific energy of existing houses in the year 2000. For doing so, the ranked specific

energy demand of each house type is multiplied with its ERFA (year 2000), see

formula below. The resulting value is compared to the RH demand calculated in the


previous section (72 PJ for SFH). Once the calculated value matches the RH

demand, the starting point of the reference specific MC curve is obtained and can be

used in our analysis. The same procedure is used to calculate the specific MC

demand of SFH and MFH.

bo o

b

tbt QhEBFDMDRH � ⋅=0,_

otDMDRH _ : RH demand for the time period t0 [PJ/a]

0,tbEBF : Reference Energy Area [Mio m2]

boQh : Specific energy demand of each house type [MJ/m2a] for the baseline

to: First year of the time horizon (year 2000)

b: Building category by construction period

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0 100 200 300 400 500 600

[MJ/m2a]

[CH

F/k

Wh

]

Before 19471947 -19751976 - 19851986 - 2000

Qhmin

Qh0

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0 100 200 300 400 500 600

[MJ/m2a]

[CH

F/k

Wh

] Before 1947

1947 -1975

1976 - 1985

1986 - 2000

Qhmin

Qh0

Figure 16: Marginal-cost curves for SFH (left) and MFH (right) existing buildings.

Each marginal cost curve has a highest value ( oQh ), reflecting the ‘specific energy

demand of each house type [MJ/m2a] for the reference case’ and a lowest value

( minQh ) reflecting the ‘specific energy demand of each house type [MJ/m2a] for best

possible renovation’. However, it can also adopt any value between the reference

case and the best possible option ( nQh ). Figure 16 shows the values oQh and

minQh for buildings constructed before 1947. Having this in mind, we can calculate the

theoretical maximum demand reduction of each house type using the formula below.

Note that the same calculation can be done for SFH and MFH.

booQhERFADMDRHDMDRH

b

tbttred min,,max_ 0__ � ⋅−=

otredDMDRH ,max__ : Theoretical maximum reduced RH demand [PJ/a]


With regards to the renovation procedure, in reality, houses can be grouped into

three different house types: houses for renovation, houses for maintenance and (so-

called) sleeping houses. Houses for renovation refer to houses, which, due to a

renovation, increase their energy efficiency. This renovation is an energetic

renovation. This means that the building code (e.g. the isolation of roofs, walls or

windows) is improved. Once the building code is improved and a house demands

less energy for heating, the building code remains untouched until a renovation is

needed again (when the end of the building-code lifetime is reached). Houses for

maintenance refer to those houses, which are renovated but not energetically

improved. The building code remains the same and the consumption of the house

remains constant. Sleeping houses refers to those houses which are not renovated

at all. In this case the owner of the house could decide to invest into a renovation at

any time.

In the baseline scenario, we guarantee that only houses subject to renovation can

improve their energy efficiency (the building code) and demand less energy for

heating. Therefore, we assume a renovation cycle or renovation rate for existing

buildings. In other words, we need to find the maximum share of houses to be

renovated for every time period. This renovation rate also corrects the theoretical

maximum reduced RH demand as calculated in the last section. Using the renovation

rate (renb,t) we can calculate the cumulative reduced energy demand until 2050,

using the formula below. In words, the renovation rates multiplied with total amount of

ERFA give us the total amount of ERFA that can be renovated during each modelling

period. Multiplying these values with the specific energy use (new specific energy

use due to renovation subtracted from the reference case) reveals the cumulative

energy savings in [PJ/a]. Table 5 depicts the renovation rate of existing buildings.

� �=

−⋅⋅=2050

20050,, )(_

t b

ntbtbcum bbQhQhrenERFADMDRH

RH_DMDcum: Cumulative reduced energy demand [PJ/a]

renb,t: Renovation rate [%]


Table 5: Five-year period renovation rates of existing buildings [%].

SFH –Existing Buildings [%]

Before 1947 1947 – 1975 1975 - 1985 1985-2000 Year

4.0% 4.5% 4.0% 1.0% 2005

4.0% 4.5% 4.0% 1.0% 2010

3.5% 4.0% 5.0% 3.0% 2015

3.5% 4.0% 5.0% 3.0% 2020

3.0% 3.5% 4.5% 3.0% 2025

3.0% 3.5% 4.5% 3.0% 2030

2.5% 3.5% 3.5% 2.5% 2035

2.5% 3.5% 3.5% 2.5% 2040

2.5% 3.0% 2.0% 2.0% 2045

2.5% 3.0% 2.0% 2.0% 2050

MFH – Existing Buildings [%]

Before 1947 1947 - 1975 1975 - 1985 1985-2000 Year

4.6% 6.6% 4.6% 1.2% 2005

4.6% 6.6% 4.6% 1.2% 2010

3.6% 5.0% 5.7% 3.2% 2015

3.6% 5.0% 5.7% 3.2% 2020

3.0% 4.0% 5.2% 3.7% 2025

3.0% 4.0% 5.2% 3.7% 2030

2.6% 3.5% 3.9% 3.3% 2035

2.6% 3.5% 3.9% 3.3% 2040

2.5% 3.4% 2.6% 2.1% 2045

2.5% 3.4% 2.6% 2.1% 2050

Reference: [69]

For the implementation in SMM, the MC curves were changed as follows. The

implementation procedure is illustrated Figure 17. The picture on the top left

represents a simplified MC curve as illustrated in Figure 16. The curve has three

steps; hence it can be improved by energy reduction measures three times. The first

step on the right-hand side represents the MC for the reference specific energy

demand of 400 [MJ/m2a]. This energy demand can be reduced to 300, 200 and 100,

which results in higher marginal costs (climbing up the MC curve). Note that a MC

curve, as depicted by the top left picture, exists for each of the four house types b. In

a first conversion step, the values of the specific RH demand, Qh, were multiplied

with the ERFA for each time period and with the corresponding renovation rates, see

top left picture and equation below. Since the MC curves were multiplied with the

ERFA of each time period, we obtained MC curves for time period. Each curve has

the same MC.

btb ntbtbn QhrenERFAQh ⋅⋅= ,,,'


tbnQh

,'

: Energy demand of each house type for each Energy Demand Level in

[PJ/a]

bnQh : Specific energy demand of each house type for each Energy Demand

Level in [MJ/m2a]

n: Energy Demand Level of the Building considered

Afterwards, the MC curves were normalized by calculating the difference of each MC

curve step; see lower picture of Figure 17 and equation below Figure 17. The MC

curve represents the additional (to the marginal costs for providing residential heat)

marginal costs nbMC , necessary to achieve a specific additional demand reduction.

Hence, according to our example, if the marginal costs increase by 0.2, we achieve a

demand reduction by 0.2 PJ/a.

0

0.2

0.4

0.6

0.8

1

1.2

0 100 200 300 400 500

Qh [MJ/m2a]

MC

0

0.2

0.4

0.6

0.8

1

1.2

0 0.2 0.4 0.6 0.8 1

Qh' [PJ/a]

MC

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.2 0.4 0.6 0.8 1

Qh [PJ/a]

MC

Figure 17: Marginal-cost curves implementation for SFH existing buildings used for the model implementation.

tbnn QhQhQhtbtb ,0 ''

,,−=

nnbnb MCMCMC ,0,, −=

tbnQh

,: Normalized energy demand


nbMC , : Normalized marginal costs

So far we have obtained MC curves for each building type b and each five-year time

period t. Each MC curve consists of steps representing a specific building code

improvement. Once the MC curves are implemented into SMM, investments in

building code improvement reduce the energy demand in the model. Taking into

account the renovation rates, we keep in mind that only a certain percentage of not

renovated ERFA can be renovated every five year time period. Thus, every five-year

time period, a specific percentage of non-renovated ERFA can undergo renovation.24

In SMM the implementation was realized using the so-called end-use process. An

end-use process satisfies each demand for energy by providing useful energy. In

case of an end-use process with an MC curve implementation, this demand is

reduced. Therefore, the MC costs had to be converted into investment cost (see

formula below). This guarantees that an investment in an improved building code

remains over the full life time of this building code. Renovations for example made in

period 2010-2015 prevail for the rest of the time horizon. In the following time periods

the model can decide whether or not it wants to renovate more not yet renovated

ERFA, which can again reduce the energy demand.

CRF

MCINV =

, with 1)1(

)1(

−+

⋅+=

t

t

dr

drdrCRF

INV: Investment Costs

MC: Marginal Costs

dr: Discount Rate

t: Life time

New buildings

With regards to new buildings we assume that only one specific average house type

can be built in every future modelling period (t = 2005, 2010, … 2050). For this

24 Note that in reality the quality of each renovation differs from house to house. In MAKRAL, when we talk about renovation and resulting building code improvements consuming less energy, we refer to the average improvements valid for a specific house building stock.


average house type we assume a constant improvement of energy demand over

time (see Figure 14). For example, the average SFH build in the year 2005 demands

270 [MJ/m2a] and in 2050 it demands 174 [MJ/m2a]25. These specific RH demand

values correspond to thick black line displayed in Figure 18. For the MC curve this

implies that not all saving options, which were available in the year 2005, are still

available in the year 2050. The options necessary for the reduction from 270

[MJ/m2a] to 174 [MJ/m2a] are already taken into consideration in the building code of

future houses. Moreover, the MC of the first energy saving step of the future MC

curve (starting at 174 [MJ/m2a]) has to begin at a new MC costs level (anInvCostn –

an-1InvCostn-1). This is due to the fact that the first MC step is the reduction from the

new reference consumption (DEnergy,n = 174 [MJ/m2a]) to the first improved

consumption (DEnergy,n - DEnergy,n-1). In other words, the MC curve of the year

2005 has to be cut horizontally (the MC have to be levelled to the reference value)

and vertically (the already taken saving measures of the reference development have

to be subtracted). This principle is shown in Figure 18 by the dotted MC curve.

Figure 18: Marginal-cost curve of new buildings SFH – sketch.

Reference: [69]

25 Values of the specific energy use corresponds to the PROGNOS assumptions of [62].


For implementation of the MC curves in SMM, the specific MC curve [MJ/m2a] is

converted to absolute values [TJ/a] by multiplying with the additional amount of

ERFA [Mio m2] built during each time period. In other words, for every time period t

the new specific MC is multiplied with the ERFA constructed during that time period

(ERFAt – ERFAt-1). Note that the MC curve obtained by this calculation only

corresponds to the dwelling constructed in the time period t. The following equation

describes the MC curve calculation of new buildings.

�=

−−⋅=2050

20051)(

t

tttt ERFAERFASMMCMCC

MCC: Marginal Cost Curve [TJ/a]

SMMC: Specific Marginal Cost Curve [MJ/m2a]

ERFA: Energy Reference Floor Area

t: Time Period

The implementation in SMM is done using end-use demand processes just like it is

done for existing buildings. Using this implementation the model can decide to either

use the building code shown in Figure 18 (according to [62]) or invest in dwellings

with an even more sophisticated building code. Once an investment is done, the

building code of a house will remain as is until the end of the time horizon.

3.4.2.4 Growth rates

In MARKAL a growth rate reflects the maximum annual growth of total installed

capacity in a period. The capacity growth is described by two parameters, GROWTH

and GROWTH_TID. GROWTH is a decimal fraction representing the maximum

annual growth. For example, a 10 % per annum growth rate is specified as 1.1. This

parameter has to be specified for each modelling time period. The second parameter,

GROWTH_TID, is the so-called seed value. It refers to the maximum amount of

capacity, which can be built in the initial period (the period of the first possible

investment). Usually GROWTH_TID corresponds to a very small capacity size. The

formula below describes how growth rates are implemented in the model code.

TIDGROWTHGROWTHCAPCAP tettet _)(,1, +⋅≥ −


GROWTH: Maxium Growth Rate

GROWTH_TID: Seed Value

In SMM it was necessary to add growth constraints to new technologies for the

heating sectors. Depending on the demand category, we define different

technological growth rates. For the demand categories that represent existing

buildings (RH1 and RH3) we define two growth rates. For technologies already

existing in the base year we assumed a maximum annual growth rate of 5 %, while

for new technologies we assumed a maximum annual growth rate of 10 % per year.

For demand categories that represent new houses (RH2 and RH3) we assume one

maximum annual growth rate of 10 % for all technologies.

3.4.2.5 Other residential-demand segments

The demand projection of Other residential demand segments (ORDS) were

estimated based on the Trend Ia26 scenario from PROGNOS.27[62] Thereby, in a first

step, we matched each SMM demand segment with the residential categories used

in [62]. In a second step, we estimated the future energy demands (useful energy

consumptions) based on the final-energy consumption of PROGNOS and the

efficiencies of each technology.[62,63,74]

Table 6 shows the estimated demand projections used in SMM. Table 2 enfolds all

demand segments including residential heating: Cooling (RC1), Cloth Drying (RCD),

Cloth Washing (RCW), Dish Washing (RDW), Other Electric (REA), Heating SFH

Existing Buildings (RH1), Heating MFH Existing Buildings (RH2), Hot Water (RHW),

Cooking (RK1), Lighting (RL1), Refrigeration (RRF), Heating SFH New Buildings

(RH3) and Heating MFH New Buildings (RH4). As can be seen in the table, most

demand segments increase slightly. The demand segment Other Electric (REA)

experiences a steep increase up the 30 PJ, which reflects the increased use of

devices such as computers, televisions sets, etc.

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

x

26 The Swiss Federal Office of Energy has released Energy-Perspective (Energieperspektiven) reports with several different scenario trends.[73] The scenario Trend Ia represents a reference development without any additional implementation of the already adopted environmental and political measurements and instruments. PROGNOS is responsible for the Energy-Perspectives for the residential end-use sector.[62] 27 PROGNOS calculates energy demands based on an ex-post (buildings constructed between 1880 and 2000) and an ex-ante (buildings constructed between 2001 and 2050) analysis. Relevant assumptions for this analysis are population development, GDP, amount of households, etc.


Table 6: End-use demand of residential demand segments [PJ].

Code28

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

RC1 5.14 5.9 6.8 7.7 8.7 10.2 11.7 12.4 12.7 12.9 13.0

RCD 1.44 1.6 1.7 1.7 1.8 1.8 1.8 1.8 1.8 1.8 1.8

RCW 4.56 5.0 5.3 5.5 5.7 5.8 5.8 5.8 5.8 5.8 5.8

RDW 1.66 1.8 1.8 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9

REA 11.51 13.3 15.2 17.3 19.5 22.9 26.2 27.8 29.1 29.8 30.1

RH1 71.41 71.8 71.6 71.6 71.4 71.3 71.0 70.9 70.8 70.6 70.5

RH3 80.19 80.6 80.1 79.6 79.0 78.2 77.0 76.4 75.8 75.2 74.6

RHW 18.73 18.7 18.4 18.1 17.9 17.7 17.4 17.1 16.9 16.7 16.4

RK1 6.01 6.4 6.7 6.8 6.9 6.9 6.9 6.9 6.9 6.9 6.9

RL1 10.23 11.0 11.8 12.4 12.5 12.4 12.1 11.3 10.5 9.7 8.6

RRF 4.43 4.5 4.6 4.5 4.4 4.2 4.1 3.8 3.6 3.5 3.4

RH2 0.00 3.9 7.3 10.0 12.4 14.6 16.4 18.0 18.8 19.6 20.2

RH4 0.00 3.3 6.1 9.4 12.5 15.2 17.7 19.5 20.6 21.5 22.3

3.4.2.6 Detailed final-energy consumption

This section describes the final-energy consumption over the whole time horizon.

The final-energy consumption is a result of the base-year calibration and the demand

projection elaborated earlier. However, it is also influenced by other factors, the so-

called Adratios. Adratios are user-defined constraints between processes, such as

capacity, investment or activity29 relations, which are not directly coded in MARKAL.

MARKAL provides the option to define maximum (UP), equality (FX) or minimum

(LO) relations. For example, an adratio relation could define the maximum share of

diesel for final-energy consumption that can be used in the residential heating sector.

Generally speaking, they allow for a gradual transition between energy carriers in

specific sectors. For more detailed information we refer to [10,11].

In SMM we defined adratio relations on the activity (fuel consumption) of various

demand categories. Here, activity refers to the final-energy fuel-share of a set of

technologies. These relations should be understood as estimates of future

thresholds. Table 7 illustrates all adratios used in the model. The table defines two

categories (I and II) for every demand segment (RHW, RK1, etc.). These categories

represent either fuels (e.g diesel, electricity, etc.) or technology devices

(Incandescent lighting, etc.). Looking at the adratios in SMM, category I is put in

relation to category II. To give an example: In the demand segment RH1 Biomass is

28 The description of the acronyms is displayed in Table 3. 29 The activity of a process reflects how much fuel is either being consumed or produced by a process. If the activity of a process is put in relation to other processes, the modeler defines a relationship of fuel being produced or consumed by one technology or a set of technologies in comparison to a larger group of technologies. Thereby, the one technology or a set of technologies must be a part of the larger group of technologies.


put into relation to all other fuels (All). Furthermore, biomass should have at least a

(minimum) share of 4 %. In other cases, we also defined fixed or upper (maximum)

shares as indicated in the column “Type”.

Table 7: Adratios residential sector.

Category I Category II Type 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Hot Water (RHW)

Natural Gas All Maximum 0.20 0.23 0.26 0.30 0.35 0.41 0.47 0.54 0.63 0.73

Diesel All Minimum 0.46 0.36 0.26 0.16 0.06 0.00 0.00 0.00 0.00 0.00

Electricity All Maximum 0.23 0.27 0.31 0.36 0.42 0.48 0.56 0.64 0.75 0.86

Cooking (RK1)

Electricity All Minimum 0.88 0.83 0.78 0.73 0.68 0.63 0.58 0.53 0.48 0.43

Lighting (RL1)

Incandescent All Minimum 0.70 0.65 0.55 0.45 0.35 0.25 0.15 0.05 0.00 0.00

Fluorescent All Maximum 0.08 0.10 0.13 0.17 0.21 0.27 0.35 0.44 0.56 0.72

Halogen All Maximum 0.08 0.10 0.13 0.17 0.21 0.27 0.35 0.44 0.56 0.72

Room-Heating Single-Family Houses Existing Building (RH1)

Biomass All Minimum 0.04 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.03


Room-Heating Multi-Family Houses Existing Building (RH2)




Room-Heating Single-Family Houses New Building (RH3)



Room-Heating Multi-Family Houses New Building (RH4)




Reference: [11,75], [62] own assumption

Section 3.3.2 already gave a general overview of the final energy consumption by

fuel and sector. In this section we additionally provide a more detailed outlook of the

final-energy consumption for every residential demand segment30. Figure 19 provides

an overview of each demand segment and the corresponding fuel usage. For

instance, the first demand segment, Cooling (RC1), shows a strong increase in the

consumption of electricity. A more differentiated picture draws the segment Heating

Single Family House New Buildings (RH1). The segment is dominated by (diesel

heating) oil and natural gas. The use of oil decreases whereas the use of natural gas 30 Note that SMM is a cost-minimization model. When interpreting future results, the reader should keep in mind that future is not ‘simulated’ but that technologies are chosen based on the lowest total system-costs. Hence, SMM advices how the technology mix should look like in a cost-optimal solution. This also applies to the reference case displayed here.


increases at the same time. Compared to RC1 where in fact electricity covers the

total energy demand, in the RH1 segment many other fuels still play a significant

role, namely biomass, electricity, etc. Note, the last picture on the right hand side of

Figure 19 shows the total consumption by fuel of the residential heating sub-sector (it

adds up RH1 to RH4).

Cooling (RC1)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassElectricity

Cloth Drying (RCD)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity

Cloth Washing (RCW)

0

1

2

3

4

5

6

7

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity

Dish Washing (RDW)

1.5

1.55

1.6

1.65

1.7

1.75

1.8

1.85

1.9

1.95

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity

Other Electric (REA)

0

5

10

15

20

25

30

35

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity

Heating SFH Existing Buildings (RH1)

0

10

20

30

40

50

60

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassCoalElectricityNatural GasOilOther

Heating MFH Existing Buildings (RH2)

0

2

4

6

8

10

12

14

16

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassElectricityNatural GasOilOther

Heating SFH New Buildings (RH3)

0

10

20

30

40

50

60

70

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassCoalElectricityNatural GasDistrict HeatOilOther


Heating MFH New Buildings (RH4)

0

2

4

6

8

10

12

14

16

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassElectricityNatural GasDistrict HeatOil

Hot Water (RHW)

0

2

4

6

8

10

12

14

16

18

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassElectricityNatural GasDistrict HeatOilOther

Cooking (RK1)

0

1

2

3

4

5

6

7

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassElectricityNatural Gas

Lighting (RL1)

0

1

2

3

4

5

6

7

8

9

10

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity

Refrigeration (RRF)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity

Total Residential Heating

0

20

40

60

80

100

120

140

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

BiomassCoalElectricityNatural GasDistrict HeatOilOther

Figure 19: Final-energy consumption of residential demand segments.

The following two figures show the detailed final-energy consumption of the

residential heating sub-sector by technology and the total final-energy consumption

of the residential sector. Figure 20 illustrates the final-energy consumption of the

heating sector. The heating sector continues to be dominated by oil and gas heating

systems. However, there is a strong tendency to switch from oil to gas heating

systems after the year 2025. The electrical consumption does not play a major role in

the heating sector. On the one hand this is due to a decreasing importance of

electrical resistance technologies. On the other hand this is due to the high

efficiencies of electrical heat pumps. All other heating technologies, especially

biomass stoves and district heating systems, remain to have a comparatively small

importance in the heating sector.


Also shown in Figure 20 is the amount of saved energy due to a better isolation of

roofs, windows, etc and the increase of the useful-energy demand. The energy

savings increase constantly over time. In 2050, the final-energy consumption due to

energy savings is lowered by 24 PJ or 15 %. Most saved energy originates from

isolating existing houses, about 70 %. New houses already have well improved

energy saving standards, hence additional savings play a smaller role. The increase

of useful-energy demand is represented by the black line. The demand increases

gradually by 24 %. Considering that the final-energy consumption remains about

constant over whole the time horizon, the demand increase indirectly represents the

energy-efficiency improvement of the baseline scenario due to improved heating

technologies.

0

20

40

60

80

100

120

140

160

180

200

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

0

0.2

0.4

0.6

0.8

1

1.2

1.4

En

erg

y D

em

an

d [

per

Un

it]

Other Heating Biomass Stoves District Heating

Electrical Resistance Heat Pump Electric Gas Heating

Oil Heating Saved Energy Energy Demand

Residential heating technologies (including saved energy & energy demand):

Figure 20: Detailed final-energy consumption of the residential heating sector [PJ]. Also depicted in the figure

is the saved energy (grey area) due to improved insulation of roofs, windows, etc and the increase of the useful-

energy demand. The energy demand (solid line) is illustrated in [per Unit], relative to the year 2000.31

Figure 21 illustrates the total final energy consumption by energy carriers, summed

over all demand segments. We see that the residential sector remains to be

dominated by fossil fuel and electricity. However, a fuel switch is taking place from

diesel heating (oil) to natural gas. Other fuels, such as biomass, remain at small

levels.

31 For the amount of final-energy saved, the author converted the useful-energy demand reduction to the final-energy equivalents. For the conversion an efficiency of 100 % is assumed.


0

50

100

150

200

250

300

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

OtherOilDistrict HeatNatural GasElectricityCoalBiomass

Energy carriers:

Figure 21: Final-energy consumption of the residential sector [PJ] by energy carriers for all demand

categories.

3.5 Description of the transportation sector

In this section we describe the base-year calibration and future projection of the

transportation sector and provide a detailed outlook of the final-energy consumption

by all transportation modes until 2050. Next to the residential sector described above,

the transportation sector is of major importance when it comes to fuel (especially

fossil fuel) consumption and energy-saving potentials. According to [1] the

transportation sector is the largest energy consumer with about 303 PJ in 2000. This

corresponds to 35 % of the total final-energy consumption in the sector. The main

challenge for the future transportation sector is to switch firstly from today’s standard

cars to highly efficient cars consuming 5lt/100 km or less. Secondly, a transformation

from internal combustion engines (ICE) using gasoline and diesel to hybrid and fuel-

cell (FC) cars using natural gas and eventually hydrogen must be realized. Next to

the heating sectors, the transportation sector offers the second largest potential to

reduce the energy consumption by introducing fuel switching and technological

changes.

In SMM, we distinguish between nine different demand segments for the

transportation sector, see Table 8. The demand of each segment is either modelled


in [PJ] or in [bvkm/a]32. Aviation and navigation transportation modes have the unit

[PJ]. Road transportation modes have the energy-demand unit [bvkm/a].

Table 8: Demand segments of the transportation sector.

Description Abbreviation Demand Unit / a

Domestic Aviation TAD PJ

International Aviation TAI PJ

Bus TRB Bvkm

Trucks TRM Bvkm

Passenger Cars TRT Bvkm

Two Wheelers TRW bvkm

Rail TTP PJ

Domestic Navigation TWD PJ

International Navigation TWI PJ

3.5.1 Base year calibration

In this section, we illustrate the base-year calibration of the year 2000. The statistical

values of the base-year calibration is based on the Swiss Overall Energy statistic.[1]

The statistic defines the total final-energy consumption of the transportation sector for

the year 2000. However, this statistic has specific limitations because it does not

elaborate on a consumption split between different transportation modes such as

passenger car, busses, truck, etc. It only states the summation of the whole

transportation sector. More detailed information can be found in the Swiss Federal

Energy Perspectives, an analysis conducted by INFRAS.[76] INFRAS models the

transportation sector with corresponding future scenarios until 2035. However, it is

essential to note one important difference between the Swiss Overall Energy statistic

and the Energy Perspectives. The Swiss Overall Energy statistic is balanced

according to the Sales Principle whereas the Energy Perspectives determine and

project energy consumptions based on the Territorial Principle (also called

Consumption Principle). A third allocation method of importance is the so-called

Inhabitant Principle. All three allocation principles can be described as follows:

• Sales Principle: This principle determines the amount of energy carriers (fuels)

sold in a country and estimates the resulting emissions. All energy carriers and

emission are allocated to this country. For instance, the emissions resulting from

gasoline tanked in Switzerland but consumed in Germany are allocated to Swiss

32 [bvkm/a] is an abbreviation of billion vehicle kilometres per year.


emissions. The Swiss Overall Energy Statistic uses this principle to allocate all

resources.[77]

• Territorial or Consumption Principle: This principle determines the amount of

energy carriers (fuels) which are consumed in Switzerland. According to this

principle gasoline bought in Switzerland but consumed in Germany account to

Germany. The resulting emissions are also allocated to Germany. INFRAS uses

this principle to allocate resources.[78]

• Inhabitant Principle: This principle distinguishes between Swiss inhabitants and

foreigners. It determines the amount of energy carriers (fuels) consumed by

Swiss inhabitants in Switzerland and abroad.[78]

In SMM, we use the sales principle based on Swiss Overall Energy Statistic.

Because some statistical data for the model calibration originates from INFRAS,

statistical adjustments are necessary to estimate the fuel-consumption shares of the

road transportation sector. All principles define exactly who consumes which energy

carriers and where those energy carriers are consumed, hence, we can also

correlate the statistics to another. Using specific assumptions, we can convert

statistics based on the territorial to statistics based on the sales principle. To obtain

the statistical values for the sales principle from the territorial principle, we have to

take into account the so-called ‘tank tourism’. Generally, because of differences in

fuel prices, a recognizable amount of people from abroad travel to Switzerland to

tank gasoline and a recognizable amount of Swiss inhabitants travel abroad to tank

diesel. For the statistical conversion we have to subtract the amount of fuel tanked

abroad but driven in Switzerland and add the amount of fuel tanked in Switzerland

but driven abroad. The method applied in this context is explained below.

For a first modal final-energy consumption split, we used the total final-energy

consumption of the transportation sector as described by the Swiss Federal Office of

Energy.[1,76] In total the transportation sector consumed 303 PJ in the year 2000. In

a first step the total consumption was separated into Rail, Road, Air and Navigation

modes using IEA statistics.[49] With a share of 74 % road transport is the major

consumer followed by air traffic having a share of 23 %. In the statistics, air transport

is determined using the sales principle and includes domestic and international

aviation. Fuel consumption by international aviation refers to fuel tanked in

Switzerland and used for international flight connections. Table 9 shows the final-


energy fuel consumption of the transportation sector. It distinguishes transportation

modes as well as fuels for the year 2000.

Table 9: Fuel consumption of the transportation sector in [PJ] in 2000.

Gasoline Kerosene Diesel Electricity Total

Rail 0.6 9.5 10.1

Road 169.0 54.8 223.8

Air 0.3 68.0 68.2

Navigation 0.5 0.5

Total 169.3 68.0 55.9 9.5 302.6

References: [49,76,79]

Having obtained the total road-transport consumption, we split the consumption into

four different modes: Cars (also referred to as Passenger Cars), Motorcycles, Buses

and Freight. In SMM, the final-energy consumption estimates for every transportation

mode and fuel underlies the equation below. Values for Stock of Vehicles, Kilometres

per Vehicles Travelled per Annum and Average Efficiency of Vehicles in 2000 are

mainly based on values from INFRAS, see Table 10, Table 12 and Table 13. As

mentioned above, INFRAS uses the territorial principle to estimate fuel consumption

whereas Swiss Overall Energy statistic uses the sales principle. Therefore, it was

necessary to exogenously adjust the stock of vehicles. In the model we carried out

stock changes as illustrated in Table 11. These changes guarantee the correct

allocation of fuel tanked abroad but driven in Switzerland and fuel tanked in

Switzerland but driven abroad. The Conversion Factors of the energy unit [PJ] to [Lt]

of gasoline and diesel are depicted in Table 14. Finally, Table 15 shows the results of

the obtained modal road split. The total road consumption adds up to 224 PJ. Cars,

with a share of 75 %, are the largest consumer, followed by freight transport with a

share of 23 %. Passenger-car transportation also constitutes the major consumer of

the whole transportation sector having a share of 55 %.

10⋅⋅⋅⋅= CFFCKVASVFEC

FEC: Final Energy Consumption [PJ]

SV: Stock of Vehicles [1000 cars] (adjusted by Tank Tourism)

KVA: Kilometres per Vehicle per Annum [Vkm/a/car]

FC: Fuel Consumption [Lt/100km]

CF: Conversion Factor [PJ/Lt]


Table 10: Stock of vehicles [1000 Vehicles].

Cars Motorcycles Busses Freight Total

Diesel 142 6.0 152

Gasoline 3402 731 0.4 160

LPG (not included) 1

Total 3545 731 6 312 4595

References: [76,80,81]

Table 11: Changes of stock of vehicles due to tank tourism [1000 Vehicles].

Cars

Gasoline +10%

Diesel -10%

Trucks

Gasoline +10%

Diesel -30%

Table 12: Kilometres per vehicle travelled per annum [Vkm/ Vehicle / a].

Cars Motorcycles Busses Freight

Diesel 18400 49000 25251

Gasoline 13900 2744 49000 14582

LPG (not included) 17500

References: [82]

Table 13: Average efficiency of vehicles 2000 [Lt/100km].

Cars Motorcycles Busses Freight

Diesel 7.73 - 24.91 24.43

Gasoline 8.76 1.70 28.56 31.26

LPG (not included) 7.73 - - -

Total

References: [76]

Table 14: Conversion factors PJ to Lt for different fuels.

Fuel PJ to Lt

Diesel 26833603

Gasoline 28618008

LPG 38976268


Table 15: Total final-energy consumption vehicles in [PJ].

Gasoline Diesel Total

Car 160.5 6.8 167.2

Motorcycles 1.2 0.0 1.2

Bus 0.2 2.7 3.0

Freight 7.2 45.2 52.4

Total 169.0 54.7 223.8

3.5.2 Future projection

For a better understanding of the future energy-demand projections in SMM, we

provide relevant information about available future transportation modes and

resulting future-demand projections.

3.5.2.1 Passenger cars

In the year 2000, passenger cars consist of two categories, gasoline cars and diesel

cars. The two car modes were powered by internal combustion engines (ICE). In the

last two years, alternatives engines drew increasing public attention, foremost the

hybrid cars. New hybrid cars combine a gasoline ICE with an electric engine. While

some car manufactures develop highly efficient ICE as a direct competitor to the

hybrid cars, other manufactures develop revolutionary engine concepts with

hydrogen fuel cells. Apparently, the future offers many plausible combinations of

exciting engines and new concepts. In SMM we have included many of those

options, which could be realistic from today’s perspective. Appendix 2 includes a list

of all future passenger cars including a description of important cost and efficiency

data. Future cars in SMM include:

Gasoline Cars: Internal Combustion Engine

Electric Hybrid

Hybrid Fuel Cell

Diesel Cars: Internal Combustion Engine

Electric Hybrid

Compressed Natural Gas Cars: Internal Combustion Engine

Electric Hybrid

Hydrogen Cars: Internal Combustion Engine

Electric Hybrid


Fuel Cell

Hybrid Fuel Cell

100%

105%

110%

115%

120%

125%

130%

135%

140%

145%

150%

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pa

ssen

ger

Cars

Dem

an

d In

cre

ase [

%]

Figure 22: Demand increase of passenger cars in [%].33

The demand projection of passenger cars is based on useful-energy demand

[bvkm/a] of the calibration year 2000 multiplied with the demand projections form

INFRAS [83]34. The useful-energy demand can be obtained by the average car

efficiency of each diesel and gasoline cars [bvkm/PJ] and the corresponding final-

energy consumption [PJ]. In the year 2000, the useful-energy demand was 58.8

[bvkm/a]. INFRAS projects the demand for passenger cars until 2035. From 2035

until 2050, the demand was projected using a logarithmic extrapolation. Over the

whole time horizon the passenger car demand increases by 42 % (see Figure 22).

3.5.2.2 Other transportation modes

Besides passenger cars the SMM model has several additional transportation modes

(demand categories) representing rail, road, air and navigation. The useful-energy

demand of each transportation mode is calculated in the same way it was done for

passenger cars, multiplying the average car efficiency and the corresponding final-

33 The value for the year 2005 has been adjusted slightly to better match the Swiss final-energy consumption statistics of the year 2005.[60] 34 INFRAS calculates future-energy demands based on bottom-up modeling and macro-economic assumptions such as GDP and population growth.


energy consumption. Note that for road transport the useful-energy unit (demand

unit) is [bvkm/a] while for all categories the demand unit is [PJ/a]. The demand driver

for each category is either the GDP or the population development. Only for the

category Two Wheeler, the demand projection was taken directly from INFRAS.

Table 16 shows energy demand in the year 2000 and the basis for the demand

projection. Figure 23 shows the demand projection for the transportation modes.

100%

110%

120%

130%

140%

150%

160%

170%

180%

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Oth

er

Tra

nsp

ort

ati

on

Mo

del

Dem

an

d I

ncre

ase [

%]

Population GDP GDP times Population INFRAS (2-Wheelers)

Figure 23: Demand increase of other transportation modes in [%].

Table 16: Demand segments of other transportation modes.

Demand Demand in 2000 Demand Unit / a Projection Basis

Domestic Aviation 3.20 PJ GDP and Population

International Aviation 64.76 PJ GDP and Population

Buses 0.28 bvkm GDP and Population

Trucks 4.38 bvkm GDP

Two Wheeler 1.20 bvkm INFRAS [83]35

Rail 10.13 PJ GDP

Domestic Navigation 0.22 PJ Population

International Navigation 0.29 PJ GDP and Population

35 INFRAS calculates future-energy demands based on bottom-up modeling and macro-economic assumptions such as GDP and population growth.


3.5.3 Detailed final-energy consumption

This section describes the final-energy consumption of the transportation sector over

the whole time horizon. The section also elaborates on the so-called adratios. As

mentioned above, adratios are user-defined constraints between processes, such as

capacity, investment or activity36 relations, which are not directly coded in MARKAL.

Table 17 illustrates all adratios used in the transportation sector. Again, the table

defines two categories (I and II) for every demand segment (TRT, TRB and TRM).

Category I is put in relation to category II. To give an example: In the demand

segment passenger cars (TRT), gasoline ICE cars are put into relation to diesel ICE

cars. They show minimum share of 94 % for the year 2005. Note that only ICE cars

are constrained by adratios. All other cars are not constrained; hence the choice of

new car models is totally flexible.

Table 17: Adratios transportation sector.

Category I Category II Type 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Passenger Cars (TRT)

Gasoline ICE Diesel ICE Minimum 0.94 0.89 0.84 0.79 0.74 0.70 0.66 0.62 0.58 0.54

Buses (TRB)

Diesel ICE Gasoline ICE Minimum 0.81 0.79 0.77 0.75 0.73 0.71 0.69 0.67 0.65 0.63

Natural Gas ICE All Maximum 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80

Trucks (TRM)

Gasoline ICE Diesel ICE Minimum 0.12 0.11 0.10 0.09 0.08 0.07 0.06 0.05 0.04 0.03

Natural Gas ICE All Maximum 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80

Reference: [63,83] own assumption37

Figure 24 provides an overview of each demand segment and the corresponding fuel

use in the transportation sector. For instance, the demand segment passenger cars

shows a strong increase in the consumption of diesel. At the same time, the

consumption of gasoline decreases and has a share of only 34 % in 2050. Apart from

passenger cars, almost all transportation modes show a clear-cut final-energy

consumption until 2050. Fuel switching to natural gas or even hydrogen does not

take place in the baseline scenario. The aviation demand-segments are still

36 The activity of a process reflects how much fuel is either being consumed or produced by a process. If the activity of a process is put in relation to other processes, the modeler defines a relationship of fuel being produced or consumed by one technology or a set of technologies in comparison to a larger group of technologies. Thereby, the one technology or a set of technologies must be a part of the larger group of technologies. 37 ICE is the abbreviation for Internal Combustion Engine.


dominated by aviation gasoline, rail by electricity and trucks by diesel (oil). Only

buses show a doubling in the use of gasoline while diesel remains at constant levels.

Domestic Aviation (TAD)

0

0.5

1

1.5

2

2.5

3

3.5

4

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Aviation GasolineJet Kerosene

International Aviation (TAI)

0

10

20

30

40

50

60

70

80

90

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Jet Kerosene

Busses (TRB)

0

0.5

1

1.5

2

2.5

3

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

DieselGasoline

Trucks (TRM)

0

10

20

30

40

50

60

70

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

DieselGasoline

Passenger Cars (TRT)

0

20

40

60

80

100

120

140

160

180

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

DieselGasoline

Two Wheelers (TRW)

0

0.5

1

1.5

2

2.5

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Gasoline

Rail (TTP)

0

2

4

6

8

10

12

14

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

DieselElectricity

Domestic Navigation (TWD)

0

0.05

0.1

0.15

0.2

0.25

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Diesel


International Navigation (TWI)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Diesel

Figure 24: Final-energy consumption of transportation demand segments.

0

50

100

150

200

250

300

350

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

ElectricityGasolineDieselJet KeroseneAviation Gasoline

Energy carriers:

Figure 25: Total final-energy consumption of the transportation sector.

Shown in Figure 25, the transportation sector remains to be dominated by oil

products. However, fuel switching takes place. While the shares of gasoline

decrease, the shares of diesel increase simultaneously. Electricity only has a little

share and alternative fuels are not of importance in the baseline.

Evaluating intermediate steps towards the 2000-Watt society 59

4 Evaluating intermediate steps towards the 2000-Watt

society

This chapter describes the main results of the 2000-Watt society analysis. During the

first half of the 21st century, only intermediate steps towards this goal can be

achieved. Until 2050, a 3500-Watt Society can be reached at maximum under the

assumption that end-use demands are inelastic to prices.38 Reaching already this

intermediate step is associated with a considerable transformation of the Swiss

energy system as we know it today and sizeable costs. Therefore, the 2000-Watt

society should be seen as a long-term goal which could possibly be reached only

during the second half of the century with radical technological changes and very

efficient energy systems. Note that the unit [Watt] in this context refers to Watt per

capita. In the following text use the abbreviation [kW/Cap], which refers to 1000

Watts per Capita.

The chapter is divided into five sections. Section 4.1 illustrates overall results of

primary-energy balances and highlights costs and CO2 emissions associated with

achieving specific consumption targets. Section 4.2 elaborates final-energy

consumption of the 3500-Watt society in detail. The section especially focuses on the

residential and transportation sectors. Section 4.3 discusses the importance of

additional scenarios with CO2 restrictions as well as combined kW/Cap and CO2

limiting scenarios. Section 4.4 scrutinizes in detail the effects of a combined scenario

targeting a 3.5 kW/Cap consumption in 2050 and a 10% CO2 reduction per decade39.

The last section draw conclusion on the obtained results.

4.1 Primary-energy balances of the 3500-Watt society

This section illustrates the overall results using Primary Energy (PE) balances. In

doing so, the author compares various scenarios using sensitivity analyses on

Primary Energy per Capita (PEC) consumptions and oil prices in the year 2050. The

sensitivity on PEC includes a non-limited PEC consumption and PEC consumption

targets of 5.0, 4.5, 4.0 and 3.5. Note that all PEC targets are implemented specifically

for the 2050. In order to avoids excess cost penalties at earlier time periods, in all

other time periods before the year 2050 no kW/Cap targets are implemented. The

38 The evaluation of a partial equilibrium model allows further primary-energy per capita reductions as the consumer response to price changes is reflected. This is discussed in the next chapter. 39 See Figure 40: CO2 emission targets for details.


model then is free to choose the investment level needed to reach the goal without

any premature phasing-out of existing capacities. The sensitivity on oil prices

comprises values of 50, 75, 100 and 125 US$2000/bbl in the year 2050.

0

1

2

3

4

5

6

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pri

mary

En

erg

y p

er

Cap

ita [

kW

/Cap

]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 26: Primary energy per capita [kW/Cap] development for various kW/Cap targets in the year 2050 at an

oil price of 75 US$2000/bbl in the year 2050.

Figure 26 shows the development of primary energy per capita (PEC) for various

kW/Cap targets at on oil price of 75 US$2000/bbl in 2050. The lowest consumption that

can be reached until 2050 is a PEC of consumption of 3.5 kW/Cap. A more stringent

target cannot be realized as of 2050. As depicted in the figure, the strongest

technological changes occur towards the end of the time horizon. The figure can be

separated into two time phases. The first phase starts in the year 2010 and lasts until

2040. The second phase mirrors the time period 2040 and 2050. In the first phase,

initial technological change must be triggered. Compared to the first phase, the

second phase is the more important one. In the second phase, profound chances40

must be undertaken in order to realize substantial reduction targets. Results for other

oil prices than 75 US$2000/bbl are illustrated in the appendix 5.1. Increasing oil prices

impact the PEC consumption only moderately to negligibly. For the non-kW/Cap-

constrained scenarios, we can observe overall PEC reduction of about 10 %

40 The profound changes are due to strong efficiency gains in the end-use sector and the replacement of nuclear power stations.


depending on the oil prices. On the contrary, oil price changes have only a negligible

impact on the PEC for all scenarios with a 3.5 kW/Cap target.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

No kW/Cap target(5.17 kW/Cap)

5.0 kW/Cap target 4.5 kW/Cap target 4.0 kW/Cap target 3.5 kW/Cap target

Pri

mary

En

erg

y [

kW

/Ca

pit

a]

RenewablesHydroNuclearNatural Gas OilCoal

Energycarriers:

Figure 27: Total primary-energy consumption for an oil price of 75 US$2000/bbl in the year 2050.

Figure 27 depicts the PEC consumption for an oil price of 75 US$2000/bbl in 2050.41 In

2050, the PEC consumption amounts to 5.17 kW/Cap for the non-constraint

scenario. All other scenarios are bounded by kW/Cap targets. At maximum a

reduction to 3.5 kW/Cap (32 %) can be achieved. Comparing the non-constraint

scenario, with the increasingly constrained kW/Cap scenarios, we see a very small

but gradual reduction of fossil energy (coal, oil and natural gas). The scenario which

gets out of the line is the 4.0 kW/Cap scenario with a strong increase in fossil energy,

especially natural gas, consumption. Even more striking is the decommissioning of

nuclear-power plants. In 2045, the last power station, Beznau II, will be

decommissioned without any nuclear replacement in the 4.0 and 3.5 kW/Cap

scenarios.42 Due to this decommissioning of nuclear-power plants combined with

investments in (high efficient) gas-turbines power stations, the overall efficiency of

the Swiss energy system can be reduced significantly and PEC consumptions of 4.0

and even 3.5 are obtained. After all, this replacement is also one of the main reasons

for the strong PEC reductions after 2040, as shown in the previous figure. The side- 41 The results for all other oil prices are shown in the appendix. 42 Nuclear power plants usually have an expected life time of 40 years. Decommissioning dates of Swiss nuclear plants and technical information about new nuclear power stations can be found in [4].


effect is raising CO2 emissions for the 4.0 KW/Cap target, see Figure 28. Also note

that we do not recognize an intensified use of renewable energies as they also

assume low conversion efficiencies like nuclear.43

No limit5

4.54

3.5

050

075

100

125

0

5

10

15

20

25

30

35

40

45

50

[Mt] CO2

[kW/Cap] Primary energy target 2050

[US$2000/bbl]

Oil price 2050

45-5040-4535-4030-3525-3020-2515-2010-155-100-5

Figure 28: CO2 Emissions of different scenarios in the year 2050.

Figure 28 illustrates the CO2 emissions of all contemplated scenarios. The x-axis

depicts the kW/Cap target, the y-axis the oil price in the year 2050 and the z-axis the

emissions in the year 2050. To understand the figure, we could for instance take the

‘not limited kW/Cap’ value at an oil price of 50 US$2000/bbl as a starting point and look

at various scenarios. The CO2 emissions in the starting point are 42.6 Mt. Going

along the x-axis we reach more stringent kW/Cap targets at an oil price of 50

US$2000/bbl. Going along the y-axis we reach higher oil prices for ‘not limited kW/Cap’

values. We can also go along the x and the y-axis to reach combined kW/Cap targets

for higher oil price. The point opposite to the starting point depicts a kW/Cap target of

3.5 for an oil price of 125 US$2000/bbl. All points connected together produce an area

as shown in the figure.

The figure shows that only for high oil prices (125 US$2000/bbl) or strong kW/Cap

constraints, a CO2 emission reduction to about 31 to 33 Mt CO2 can be reached in

2050. This reduction is approximately equivalent (little higher) compared to the 5 %

43 Renewable energies refer to biomass, wind, geothermal, solar, etc. Hydro power is not included in this category but listed separately.


per decade emission decrease (as illustrated in Figure 40, section 4.3). For all other

oil prices and kW/Cap constraints, the emissions are higher. Moreover, to reach

strong emission reductions, such as a 10 % per decade reduction, additional

measures are needed.

4.2 The role of end-use sectors in the 3500-Watt society

In this section the technological options to achieve a 3500-Watt society are

described. In doing so, we firstly look at the general transformations of all end-use

sectors. Secondly we scrutinize the technological modification of the residential and

transportation sectors in detail.

0

100

200

300

400

500

600

700

800

900

1000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 29: Total Final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 75

US$2000 in 2050.

Figure 29 presents the development of total final-energy (FE) consumption for

various kW/Cap PEC constraints. All trajectories account for an oil price of 75

US$2000/bbl in the year 2050. Compared to the PEC consumption development, the

FE consumption resembles a relatively smooth and constant transition over time. The

stronger the PEC target, the more energy-efficiency measures are implemented in all

end-use sectors. Especially for the 3.5 kW/Cap scenario drastic but gradual

technological changes are undertaken.


Buildings and transportation are the most energy consuming end-use sectors in

Switzerland. Each of the sectors has a different reduction potential. All energy

reductions added up attain the reduction displayed in the previous figure. The largest

reduction experiences the residential sector, closely followed by the commercial

sector. In both sectors the major reduction is accomplished by reducing heating

losses. In the transportation sector we realize rather moderate but noteworthy

efficiency gains. In the industrial and other sectors44 rather small efficiency gains are

estimated. Looking for instance at an oil price of 75 US$2000/bbl and 3.5 kW PEC use,

the residential sector reduces the final-energy consumption by 81 PJ (~ 9 % of the

total FE consumption), the commercial sector by 63 PJ (~ 7 %), the transportation

sector by 50 PJ (~ 6 %), the industrial sector by 25 PJ (~ 3 %) and all other sectors

by 4 PJ (< 1 %) in relation to the non-kW/Cap constraint scenario.

The PEC use shows rather modest oil-price sensitivities for strong kW/Cap targets.

The same modest sensitivity accounts for the FE consumption. Looking at the FE

consumption reduction over time, we recognize a maximum FE-consumption

difference in the year 2030. However, this difference becomes increasingly smaller in

time periods after 2030. In the year 2050, when the 3.5 kW/Cap target is reached,

the oil price ceases to have influence on the energy and technology mix. A 3.5

kW/Cap target demands technologies of such high efficiencies that even high oil

prices do not impact the mix further. Total FE consumption developments over time

as well as detailed sectorial and fuel consumptions for other oil prices in 2050 are

attached in the appendix 5.2.

In the remaining part of this section we focus on the technological changes of the

residential and transportation section. As mentioned above, these two sectors are of

major importance when Switzerland targets the 3500-Watt society in the year 2050.

The residential sector

The residential sector has the largest energy saving potential of all end-use sectors

in Switzerland. The consumption is heavily dependent on the oil price and on the

kW/Cap target to be achieved. Figure 30 illustrated the final-energy consumption of

the residential sector for different oil prices and the kW/Cap targets in 2050. The x-

axis depicts the kW/Cap target, the y-axis the oil price in the year 2050 and the z-axis

44 Other Sectors comprice the agriculture, non-energy use and other non-specified energy sectors.


the total-FE consumption. To understand the figure, we could again exemplarily

choose the ‘not limited kW/Cap’ value at an oil price of 50 US$2000/bbl as our starting

point and look at various scenarios. The final-energy consumption in the starting

point is 237 PJ. Going along the x-axis we reach stronger kW/Cap targets at an oil

price of 50 US$2000/bbl. Going along the y-axis we reach higher oil prices for ‘not

limited kW/Cap’ values. We can also go along the x and the y-axis to reach combined

kW/Cap targets for higher oil price. The point opposite to the starting point depicts a

kW/Cap target of 3.5 for an oil price of 125 US$2000/bbl. All points connected together

produce an area as shown in the figure.

At maximum, the consumption can be reduced to about 102 PJ. This reduction is

optimal for a high kW/Cap constraint of 3.5, independent of the oil price. Compared

to a non-kW/Cap constrained future at an oil price of 75 US$2000/bbl, this would imply

a reduction of 80 PJ or 45 %. Note ‘the stronger the PEC reduction target the less

dependent is the consumption on the oil price’ also accounts for the residential

sector.

No limit5

4.54

3.5

50

75

100

125

0

25

50

75

100

125

150

175

200

225

250

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

[kW/Cap]

Primary energy target 2050

[US$2000/bbl]

Oil price 2050

225-250200-225175-200150-175125-150100-12575-10050-7525-500-25

Figure 30: Total final-energy consumption of the residential sector in 2050.

The residential sector consists of various demand segments as described in the

chapter 3, heating, cooling, cooking etc. With regards to the utilization of energy-

reduction potentials, the most important segment is residential heating (RH). The RH

consumption for various oil prices and kW/Cap targets in the year 2050 is depicted in


Figure 31. Again, the figure has three axes. The x-axis illustrates the kW/Cap target,

the y-axis the oil price in the year 2050 and the z-axis the total-FE consumption. The

maximum reduction at an oil price of 75 US$2000/bbl is 70 PJ. At this oil price, this FE

reduction of the RH sector corresponds to 85 % of the total FE reduction of the whole

residential sector. As shown in the previous figure, the more stringent the kW/Cap

targets, the less elastic is the final-energy consumption to the oil price. For a 3.5

kW/Cap target, the final-energy consumption of RH is about 43 PJ.

The reduction of FE is strongly correlated to the reduction of CO2 emissions in the

residential sector. Putting side by side the non-kW/Cap limited scenario and the 3.5

kW/Cap target scenario for an oil price of 75 US$2000/bbl, we identify a CO2 emission

reduction of little more than 85 %. With CO2 emissions of only 0.8 Mt in the 3.5

kW/Cap scenario, the residential sector is basically CO2 free in 2050.

No limit5

4.54

3.5

50

75

100

125

0

20

40

60

80

100

120

140

160

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

[kW/Cap]


[US$2000/bbl]

Oil price 2050

140-160120-140100-12080-10060-8040-6020-400-20

Figure 31: Total final-energy consumption of the residential heating sector.

Energy, specifically RH, can be reduced by switching to more efficient technologies

or by investing into energy efficiency devices. For this purpose energy saving

options, using the marginal abatement approach, were implemented in the model,

see chapter 3. Figure 32 shows the total amount of saved energy coming from

energy-saving measures for various scenarios. The figure has three axes. The x-axis

illustrates the kW/Cap target, the y-axis the oil price in the year 2050 and the z-axis

the total amount of useful energy saved. Note that kW/Cap targets and oil prices are


in reversed order compared to previous figures. At an oil price of 50 US$2000/bbl

without any kW/Cap constraints, the useful energy reduction amounts to 25 PJ or

about 13% of the total useful-energy demand. This demand includes RH for new and

existing buildings as well as SFH and MFH. In the most constrained scenarios, with a

kW/Cap target of 3.5, the useful-energy reduction nearly doubles to more than 45 PJ.

As can be seen in the figure an oil price increase alone already has a strong

influence on the amount of energy reduced. In comparison, a significant kW/Cap

target, impacts the amount of reduced energy due to the implementation of energy

saving measure even more drastically.

No limit5

4.54

3.5

50

75

100

1250

5

10

15

20

25

30

35

40

45

50

Fin

al-

En

erg

y S

avin

gs [

PJ]

[kW/Cap]


[US$2000/bbl]

Oil price 2050

45-5040-4535-4030-3525-3020-2515-2010-155-100-5

Figure 32: Final-energy savings of the residential sector in 2050.

Using the following two figures, we elaborate in detail the structural changes

necessary to achieve the energy saving reduction illustrated in the last figure. We

choose an oil price of 75 US$2000/bbl in the year 2050. Based on this oil price, we

choose two scenarios, one without any kW/Cap target and one with a kW/Cap target

of 3.5. Figure 33 and Figure 34 show the specific energy demand of all house types

modelled for the two scenarios. Looking at the figure, we can identify two main

results. Firstly, average new buildings consume much less energy than average

existing buildings. The entire existing building stock in Switzerland encompasses a

specific energy demand between 350 and 400 MJ/m2, which improves gradually over

time. On the contrary, new buildings should have high insulation standards.


Depending on the scenario and the house type, the specific energy demand ranges

between 140 and 200 MJ/m2 in the year 2010. Note that due to modelling constraints,

we consider house built in the year 2005 as new houses.45 In our scenarios, an

average new building should ideally demand less than half of the energy of the

average existing building.

0

50

100

150

200

250

300

350

400

450

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Sp

ecif

ic E

nerg

y D

em

an

d [

MJ/m

2]

Existing SFHExisting MFHNew SFHNew MFH

Figure 33: Specific-heating demand of an average residential house for an oil price of 75 US$2000/bbl and

without a primary energy constraint.

Secondly, we notice a major difference between the two scenarios with respect to

possible demand reductions of the various house types. Whereas the average

demand of existing buildings is additionally reduced by about 20 PJ (e.g. existing

SFH reduces from 340 MJ/m2 to 320 MJ/m2), the average demand is additionally

reduced by around 60 PJ for new buildings (e.g. new SFH reduces from more than

170 MJ/m2 to less than 115 MJ/m2). Yet, the additional reduction of 20 PJ implies a

tremendous effort to improve the existing building stock insulation because, on the

one hand, only about 30 % of the existing building stock can be renovated in 50

years and because, on the other hand, the absolute reduction is much higher (e.g for

existing SFH of less than 400 MJ/m2 to less than 320 MJ/m2).

45 Note that due to modelling constraints, we consider houses built in the year 2005 as new houses.


0

50

100

150

200

250

300

350

400

450

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Sp

ecif

ic E

nerg

y D

em

an

d [

MJ/m

2]

Existing SFHExisting MFHNew SFHNew MFH

Figure 34: Specific-heating demand of an average residential house for an oil price of 75 US$2000/bbl and a

primary energy constraint of 3.5 kW/Cap.

Figure 35 depicts the over-time final-energy consumption of the RH sector for an oil

price of 75 US$2000/bbl and a kW/Cap target of 3.5. The consumption reduces from

nearly 168 PJ to 44 PJ, or about 74 %. While in the first 25 year fossil technologies

still dominate the RH sector, in the second quarter of the century, fossil energy loses

importance drastically. Heat pumps and district heating systems start to dominate the

market more and more. In 2050, the penetration of these technologies is strong

enough such that fossil based-technologies lose all their market shares. The RH

sector is basically CO2 free. In the figure, we can also see the amount of saved

energy due to an increasing utilization of energy-saving option. Note that the

depicted amount of saved energy just fulfils an illustrative purpose and is estimated

using an useful to final energy conversion factor of 100%.


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Other Heating Biomass Stoves District Heating Electrical Resistance

Heat Pump Electric Gas Heating Oil Heating Saved Energy

Residential heating technologies (including saved energy):

Figure 35: Detailed final-energy consumption of the residential heating sector [PJ] for an oil price of 75

US$2000/bbl and a primary energy target of 3.5 kW/Cap in 2050.

Figure 36 compares the per unit increase/decrease of useful-energy demand (UED),

final energy (FE) consumption and ERFA (Energy Reference Floor Area). In

Switzerland a sizeable amount of new buildings will be constructed. As a result the

ERFA constantly increases over time. On the contrary, we see the UED decreasing

over time. Instalments of energy-saving measurements in Swiss households

constantly rise. Each energy-saving instalment (energy conservation in buildings)

reduces the specific energy demand, which in the end reduces the total UED.

Without any installations of energy-saving measures, the energy demand would

increase proportionally to the ERFA. At the same time, the final-energy consumption

reduces drastically to about 25 % of the consumption in the year 2000. Additionally to

the reduced demand, investments into high-efficient end-use technologies and fuel

substitution show an effect here, see previous figure.


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%]

Energy Demand Final Energy Consumption ERFA

Figure 36: Comparison of energy demand, final energy consumption and ERFA for an oil price of 75

US$2000/bbl and a primary energy target of 3.5 kW/Cap in 2050.

The transportation sector

The second end-use sector the author contemplates in detail is the transportation

sector. Again, at first we illustrate a general consumption overview before going into

details of the passenger car sector being the major energy consumer.

Figure 37 shows the total final-energy consumption in the year 2050 for various oil

prices and kW/Cap targets. For no kW/Cap target scenarios, the FE consumption

remains relatively stable. Only for very high oil prices, we see a reduction of the total

consumption.46 Therefore, despite oil-price increases the total efficiency of the

transportation sector does not improve significantly. The contrary effect is observed

looking at severe kW/Cap targets. Reaching a FE consumption of about 250 PJ, the

sector undergoes an energy-efficiency improvement of around 20 %. Note that in

general we witness a notably lower energy reduction over time in the transportation

sector compared to the residential sector.

46 Note that the price elasticity assumed to be zero for this particular analysis.


No limit5

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[US$2000/bbl]

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2050

300-320280-300260-280240-260220-240200-220

Figure 37: Final-energy consumption of the transport sector in 2050.

The same energy-reduction effect, we observe for the total FE consumption in the

transportation sector, we also see looking at passenger cars, see Figure 38. For high

oil prices, without any kW/Cap targets, the consumption reduced by only 10 PJ.

Scenarios with (or combination with) high kW/Cap targets undergo consumption

reductions to less than110 PJ.

Reaching stringent kW/Cap targets imply on the one hand energy-consumption

reductions and on the other hand a complete modernisation of the present

passenger-car fleet. Figure 39 shows the detailed implication of a 3.5 KW/Cap target

for an oil price of 75 US$2000/bbl. Currently we see a domination of gasoline and

partially diesel fuelled internal-combustion-engines (ICE) cars. Over time this

domination declines and we can identify three distinct effects. Firstly, gasoline fuelled

cars are reduced to marginal amounts. Secondly, ICE cars are replaced by the hybrid

technology. Hybrid diesel and hybrid natural gas cars have the largest market shares

in 2050. Gasoline hybrid cars only play a minor role due to the comparatively low

efficiency. Thirdly, hydrogen cars start to take off, having an initial market penetration

in 2045.


No limit5

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Figure 38: Final-energy consumption of passenger cars in 2050.

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Hydrogen Fuel CellHydrogen HybridNatural Gas HybridGasoline HybridGasoline ICEDiesel HybridDiesel ICE

Engine drives:

Figure 39: Detailed final-energy consumption of passenger cars [PJ] for an oil price of 75 US$2000/bbl and a

primary energy target of 3.5 kW/Cap in 2050.47

47 ICE refers to Internal Combustion Engine.


4.3 Importance of alternative future scenarios with carbon (CO2)

restrictions

The results presented so far emphasise on the evaluation of the intermediate steps

towards the 2000-Watt society for various oil prices. The question remains how

beneficial in terms of CO2 emissions and costs the vision of a 2000-Watt society is for

Switzerland? Therefore, in this section we analyse alternative CO2-restricting

scenarios and compare these to the results presented above. These CO2 restrictions

are implemented in combination with kW/Cap restrictions as well as without a

kW/Cap target (only CO2 emissions are limited). In this section, the author elaborates

and draws conclusions based on this all-embracing sensitivity analysis on kW/Cap

and CO2 targets as well as based on costs to the society.48 Results are focused on

selected but comprehensive PEC energy balances due the amount of data generated

by the model. Detailed results can be found in the appendix 5.

20

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Mt]

Past emissionsBaseline emissionsKyoto target reduction5% reduction constraint10% reduction constraint

Swiss Kyoto target in 2010

Figure 40: CO2 emission targets.

48 Costs in this context refer to the discounted sum of the annual costs minus revenues. They are calculated as follows: Investment costs + Costs for sunk material during construction time + Variable costs + Fix operating and maintenance costs + Surveillance costs + Decommissioning costs + Taxes – Subsidies - Recuperation of sunk material - Salvage value.


Figure 40 depicts CO2 emissions49 of the baseline scenario and of the CO2 restricted

scenarios. In the baseline scenario (‘Baseline Emissions’), the emissions increase to

more than 45 Mt in 2005 and in 2010 and decrease thereafter. According to the

baseline scenario, in the year 2050 Switzerland will reach the CO2 emission level of

the year 1990. However, even by reaching this target, Switzerland still fails to

achieve the Swiss Kyoto commitments - a 10 % reduction of the 1990 levels by

2010.[3] Additionally, the figure illustrates two policy scenarios with constraints on

CO2 emissions. In all scenarios, the author assumes that Switzerland meets the CO2

Kyoto target in the year 2010. Afterwards, a reduction of 5 and 10 % per decade is

assumed. The 5 % per decade reduction is comparable to a ‘Kyoto forever’ emission

reduction. In the following paragraphs we refer to the scenarios as 5 % and 10 %

reduction scenarios.

Figure 41 shows on the left-hand side the baseline scenario with an oil price of 50

US$2000/bbl in the year 2050. This scenario excludes any CO2 and any kW/Cap

constraints. The baseline is compared to two additional scenarios, the first with a 3.5

kW/Cap constraint, the second with a CO2 reduction target (limit) of 5 %. The

baseline PEC consumption is 5.34 kW/Cap. Switzerland is dominated by fossil fuels

and nuclear as well as hydro power. Fossil fuels, with a total share of 55 %, are the

largest contributor to the PEC consumption. Renewables only play a subordinate role

with a share of less than 6 %.

The implementation of a 3.5 kW/Cap Society, without any CO2 constraints, results in

a PEC reduction of 35 %. However, this constraint (cost-optimally) shows only a

moderate decrease of fossil fuels from 2.91 to 2.35 kW/Cap, or 19%. The energy

system still largely depends of fossil fuels. Despite that the total amount of fossil-

energy use slightly decreases, the share of fossil increases to 67 %. Neither

renewable energies (renewables) nor nuclear power are supported by this target.

Energy-efficiency improvements and the implementation of energy saving measures

play an important role. A positive aspect is the obtained CO2 emissions by reducing

the PEC consumption to 3.5 kW/Cap. The emission reduction nearly corresponds to

a 5 % reduction scenario.

49 In this context CO2 emissions are energy-related CO2 emissions as presented by the Swiss Federal Office of Energy [1]. The reader should bear in mind that the energy-related CO2 emissions of the year 2000 have been calibrated to the figures reported by [1], i.e. 44.4 Mt CO2. Therefore, they differ from the CO2 emissions estimated by FOEN [3] following the principles of the CO2 law and the Kyoto protocol.


Targeting a CO2 reduction of 5 % (per decade) leads to a much higher PEC

consumption compared to the kW/Cap scenario. The consumption reduces only

slightly from 5.34 to 4.88 kW/Cap. Thereby, the reduction of fossil fuels is similar to

the 3.5 kW/Cap scenario. In comparison to the kW/Cap scenario, we see a larger use

of oil products and a reduced use of natural gas. Furthermore, renewables are

supported by this scenario to a large extent. The amount of renewable energies

consumed nearly doubles compared to the baseline. This compensates for the higher

use of oil and oil products. Nuclear energy remains constant like in the baseline

scenario.

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Pri

mary

En

erg

y [

kW

/Cap

ita

]

Other RenewablesHydroNuclearNatural Gas OilCoal

Energy carriers:

Figure 41: Primary energy per capita [kW/Capita] for an oil price of 50 US$2000/bbl in 2050.

Looking at the illustrated scenarios, we come to the following conclusion. If the aim is

to reduce emissions moderately (by 5 % per decade) and (by doing so) the

dependency on fossil fuels, there are two options to accomplish this target.50 The first

option is to target a reduction of the PEC consumption. By increasing the overall

efficiency of the energy system, the emissions obtained nearly correspond to the 5 %

reduction scenario. In this scenario, the PEC consumption is lowered by about 35 %

and the final-energy consumption by about 18 %. Note that the high PEC reduction

levels are also due to switching from nuclear reactors to (high efficient) gas turbines.

50 This target also resembles a ‘starting point’ to become independent of fossil fuel. To achieve a noticeable independence more severe objectives must be targeted.


The second option is to enforce a CO2 emission limits of 5 %. The effect is a stronger

utilization of biomass technologies and the introduction of new nuclear-energy plants,

provided there is an appropriate political support. The overall energy-efficiency of

Switzerland must also be improved in this scenario; nevertheless, not to the same

extend as in the 3.5kW/Cap scenario.

An important question circles around the additional costs to achieve the energy

consumption associated with the illustrated scenarios. In the model the additional

cost is expressed as the ‘additional total discounted energy-system cost’. To achieve

a CO2 reduction as enforced by the 5 % reduction scenario is cheaper than to realize

a 3.5 kW/Cap society in 2050, see appendix 5.4. If the two targets were to be

combined (a 5 % CO2 reduction and a 3.5 % kW/Cap society), the costs to reach this

combined target is even higher. In fact it would be cheaper to reach a 10 % CO2

reduction, without a kW/Cap target, than to reach the combined 5 % CO2 and 3.5

kW/Cap target.51 Therefore, by just looking at the costs a kW/Cap is questionable.

Influence of the oil price

In the following paragraphs, we look at the influence of oil prices on the results

obtained so far. In order to get a clear picture, we compare several scenarios in

Figure 42. On the one hand, we contrast the baseline scenario with a scenario

having the same assumptions, except for a higher oil price. In other words, the two

scenarios do not include CO2 reductions and do not include kW/Cap targets. They

can be referred to as the ‘no constraint’ scenarios. On the other hand, we contrast

two ‘high constrained’ scenarios. These scenarios have both a strong CO2 reduction

target of 10 % as well as a 3.5 kW/Cap target. Again the difference between the two

scenarios is the oil price of 50 and 100 US$2000/bbl respectively.

On the one hand, the ‘no constraint’ scenarios reveal an apparent difference when

the results are compared to each other. When the oil price increases from 50 to 100

US$2000/bbl we see a reduction of the primary-energy consumption of 7%. Especially,

the fossil consumption reduces by 18% and use of the renewable energies increases

by 46%. On the other hand, the ‘high constrained’ scenarios show only relative

insignificant changes of the energy system when we compare these to the changes

of the ‘no constraint’ scenarios. For an oil price increase from 50 to 100US$2000/bbl,

51 This result is obtained independently of the oil price, as explained below.


we can identify an increase in the use of gas by 4% and a reduction of oil and oil

products by 3%. Generally the conclusion can be drawn, the more constrained

scenarios are (CO2 and kW/Cap) the less influential is the oil price on the Swiss

energy system.

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CO2 reduction of 10%per decade

Oil Price of 50US$2000

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Oil Price of 50US$2000

Oil Price of100US$2000

Pri

mary

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y [

kW

/Cap

ita]


Energy carriers:

Figure 42: Primary energy per capita [kW/Cap] consumption for oil prices of 50 and 100US$/bbl2000, no and

10% per decade CO2 reductions as well as no and 3.5kW/Cap primary energy constraints.

Influence of the carbon (CO2) constraint

As seen in Figure 41, the results augment an intensified use of renewables and a

constant contribution of nuclear energy for moderate CO2 constraints. On the

contrary, kW/Cap targets rather favour energy-efficiency measures. The question

remains, what is the influence of strong CO2 constraints? This can be best explained

by looking at combined CO2 and kW/Cap targets, see Figure 43. The figure depicts

the PEC consumption for an oil price of 75 US$2000/bbl52, a 3.5 kW/Cap target and

intensifying CO2 limits. In the kW/Cap scenario without CO2 limits, the results nearly

reach a 5 % CO2 reduction automatically as explained above. This is the reason why

the first two scenarios on the left hand side of the figure show similar results.

However, if Switzerland aims at more profound emission reductions in the 2050, we

52 For strong scenario constraints the obtained results are only little sensitive to the price of oil in the year 2050.


see substantial changes of the Swiss energy system. Compared to the non-CO2

constrained scenario, in the 15 % CO2 reduction scenario the amount of renewables

increases by a factor of 3.5. Nuclear energy becomes increasingly indispensable.

The use of fossil fuels, especially natural gas, reduces significantly. Fossil energies

reduce from 2.35 to 1.36 kW/Cap, which is equivalent to a 42 % reduction. Thus,

even at the kW/Cap constraint of 3.5, CO2 emissions can still be reduced by

switching to cleaner technologies. However, this is only possible at a sizeable cost

(see total-system cost increase in appendix 5.4).

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]


Energy carriers:

Figure 43: Primary energy per capita [kW/Cap] consumption for an Oil Price of 75 US$/bbl2000, various CO2

limits and a primary per capita constraint of 3.5kW/Cap.

4.4 Energy balances of the 3500-Watt society with a 10% per

decade CO2 restrictions

In the last section we saw that PE fuel-consumption shares vary depending on the

CO2-reduction target even if the total PE consumption is constrained to the same

level. Therefore, in this section we examine the effects of combined kW/Cap and CO2

targets in detail. For the analysis we exemplary choose an oil price of 75 US$2000/bbl

in the year 2050. Additionally we selected the strongest possible kW/Cap constraint

in the year 2050 (3.5 kW/Cap) and a CO2 target equivalent to a 10 % reduction (per


decade). The results obtained by this analysis are compared with scenario results of

the previous sections.

Primary-energy balances

Figure 44 compares the over time PEC consumptions of the 3.5 kW/Cap and 10 %

CO2-reduction scenarios to the reference case. The reference case has neither CO2

nor kW/Cap targets. In 2050, the reference case has a PEC consumption of 5.32

kW/Cap, while both other scenarios reach 3.5 kW/Cap. Despite the fact that both

kW/Cap limited scenarios have the same PEC consumptions in 2050, the PEC

consumptions of the two scenarios vary significantly in earlier time periods. The 10 %

CO2 reduction scenario has a lower consumption before 2050. Investments into more

efficient technologies are necessary already during the first quarter of the century.

Moreover, despite the equal amount of PEC consumption of the two kW/Cap target

scenarios in the year 2050, the fuel consumption shares differ largely. In order to

reach high CO2 reductions and strong kW/Cap target, the energy mix consists of

more renewable energies and nuclear power as well as less fossil fuels, see

appendix 5.1. Oil products are substituted by natural gas to a large extent.

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No CO2 limit and no No kW/Cap target "reference case"

No CO2 limit with a 3.5 kW/Cap target

CO2 reduction of 10% per decade with a 3.5 kW/Cap target

Figure 44: Primary energy per capita [kW/Cap] development for various kW/Cap and CO2 targets in the year

2050 at an oil price of 75 US$2000/bbl in the year 2050.


Final-energy balances and the end-use sectors

The FE consumption development between 2000 and 2050 shows similar effects

compared to the PEC consumption. In the year 2050 the FE consumption of both 3.5

kW/Cap scenarios is around 650 PJ. However in earlier time periods, the scenario

with a 10 % CO2 reduction target has a lower total FE consumption. Looking at the

FE fuel share, we see a shift of fuels. Especially the use of oil products reduces,

while the use of natural gas and renewable energies increases, see appendix 5.2.

This is the direct consequence of technological changes in the end-use sectors,

which can be best illustrated by looking at the residential and transportation sector

and more specifically at the RH technologies and the passenger car modes.

Figure 45 shows the FE consumption of the RH sector for the 3.5 kW/Cap and 10 %

CO2 reduction scenario. Already during the first quarter of the century, we observe

strong reductions of the FE consumption. Compared to the scenario without any CO2

reduction targets (see previous section), in the year 2020 the consumption amounts

to less than 100 PJ instead of 132 PJ. The amount of fossil-heating systems reduces

drastically. Ten year later, the RH heating sector is independent of oil heating

systems. The rising market penetration of heat pumps and district-heating systems is

unavoidable. Additionally, the amount of saved energy originating from improved

insulation standards is higher. Using a useful to final conversion efficiency of 100%,

the amount of saved energy grows from 44 to 53 PJ in 2050.

Figure 47 depicts the reduction of FE consumption and compares it to the per unit

increase/decrease of energy demand and ERFA (Energy Reference Floor Area).

While the ERFA constantly increases over time, the energy demand and the FE

decrease remarkably. Compared to Figure 36 (an analysis of the scenario with a 3.5

kW/Cap target but without CO2 reduction goals), the energy demand reduces further

to 89% of the current (year 2000) energy demand. To reach this target, significant

energy-saving measures must be taken as soon as possible in Switzerland.


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Heat Pump Electric Gas Heating Oil Heating Saved Energy

Residential heating technologies (including saved energy):

Figure 45: Detailed final-energy consumption of the residential heating sector [PJ] for an oil price of 75

US$2000/bbl, a primary energy target of 3.5 kW/Cap in 2050 and a CO2 reduction target of 10 %.

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Figure 46: Comparison of energy demand, final energy consumption and ERFA for an oil price of 75

US$2000/bbl, a primary energy target of 3.5 kW/Cap in 2050 and a CO2 reduction target of 10 %.

Comparably to the changes in the RH sector, the passenger car sub-sector also

undergoes structural changes when CO2 emissions are limited additional to the 3.5


kW/Cap target. As anticipated, we observe only small energy-efficiency gains of 3%

in the year 2050 compared to the non-CO2 limited scenario. The 3.5 kW/Cap already

promotes high efficiency gain without CO2 limits. Yet, the additional CO2 restriction

fosters an earlier and more profound readiness for marketing of natural gas and

hydrogen cars. In the year 2020 natural gas (ICE and Hydrid) cars have a total share

of 15 % consuming 24 PJ of FE in total. Simultaneously, the share of gasoline

decreases. High efficient diesel ICE and hybrid cars increase their shares until 2040.

Especially diesel and natural gas hybrid cars will play an important role in 2050.

Knowing that cars fuelled by hydrogen largely represent a future technology for the

second half of this century, the hybrid and fuel cell versions have a stronger and in

addition earlier market penetration. Five year earlier than in the non-CO2 limited

scenario, in the year 2040, we view the first introduction of hydrogen cars.

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H2 Hybrid Fuel CellH2 Fuel CellH2 HybridNatural Gas HybridNatural GasGasoline HybridGasoline ICEDiesel HybridDiesel ICE

Engine drives:

Figure 47: Detailed final-energy consumption of passenger cars [PJ] for an oil price of 75 US$2000/bbl and a

primary energy target of 3.5 kW/Cap in 2050 and a CO2 reduction target of 10 %. 53

Electricity balances

A prime example for an efficient substitution of fossil energy with electricity is heat

pumps. Also in industrial processes electricity can often substitute oil products and

53 ICE refers to Internal Combustion Engine. H2 refers to Hydrogen Cars.


natural gas. As can be seen in Figure 48, strong CO2 reductions increase the

electricity production and therefore the share of electricity in end-use sectors rises. A

CO2 reduction equivalent to 10 % per decade results in an electricity production

increase of more than 30 % compared to the year 2000. Excluding the amount of

electricity which was exported in 2000, we observe an increase of more than 45 % by

2050. In any case, the electricity production will increase from a today’s level of 57

TWh to 70 -85 TWh in 2050 even with a PEC consumption reduction to 3.5 kW/Cap,

which is mainly due to the extensive use of heat pumps in buildings (see Figure 46).

Current debates on nuclear power increasingly rise public awareness of whether or

not Switzerland should invest in new nuclear power station or alternative natural gas

CHP plants.[84,85] Analyzing this aspect from a cost-optimal point of view, we obtain

specific results. Without any CO2 and PEC constraints, nuclear power is visibly the

most competitive option for electricity production. The same results are attained by

implementing CO2 reduction targets. However, the option of nuclear power

disappears for strong PEC constraints. The reason is the comparably low efficiency

of nuclear power stations. Conventional and especially co-generation plants produce

electricity (and heat) with much higher efficiencies. While co-generation plants can

have an overall efficiency of up to 75 %, conventional electricity generation

technologies have efficiency around 50 %. [86,87]. However, existing nuclear power

stations have an efficiency of only 33% which might be increased to 44% in the

future, depending on the reactor type.[51,88]

The figure also shows that the technology mix for the production of electricity may be

not only determined by defining a CO2 reduction and PEC target separately. An

effective measure against climate change is especially the 10 % CO2 reduction

combined with a PEC target. This target demands massive investments in renewable

energies and a continuing reliance on nuclear energy. At the same time, the hydro

power potential should be used to the full possible extent.


-10

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90Year 2000 Year 2050 Year 2050 Year 2050 Year 2050


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No CO2 limit CO2 reduction of10% per decade No CO2 limit


Ele

ctr

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y P

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ucti

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[T

Wh

]Solar Power

Wind Turbines

BiomassCogenerationNatural GasCogenerationThermalCogenerationBiomass Thermal

ConventionalThermal and OthersNuclear Power

Hydro Power

Net Imports


Figure 48: Electricity production [TWh] for an oil price of 75 US$2000/bbl and various CO2 emission and

primary energy targets.

Renewable technologies54

Sustainability is an attempt to provide the best outcomes for the human and natural

environments both now and into the indefinite future.[90] In this context renewable

energies and their conversion products are indispensable and should be used to the

maximum possible extent. Nevertheless, sustainability does not include financial

aspects; hence renewable-energies products generated in a sustainable manner are

most often cost-effective only under a specific framework of regulations. From a

macroeconomic cost-optimal point of view the exploitation of renewable energies in

Switzerland varies strongly – with the exception of hydro power. Of all renewable

technologies hydro power is the most cost-effective technology. In all scenarios the

total additional hydro-power potential is fully used. Figure 49 illustrates the PE

consumption of renewable energies for various oil prices and CO2 emission reduction

targets.

The consumption of renewable energies rises in all scenarios compared to 2000

levels. Moderate increases of 32 % until 2050 are realized for the non CO2 and non

54 Resources that are regenerative or for all practical purposes cannot be depleted.[89]


kW/Cap limited scenario, see column two. The strongest increase we observe for a

CO2 limit of 10 %. In this scenario, the PE consumption of renewable energies rises

by more than 75 % compared to 2000 levels. In total renewable energies add up to a

PE-consumption share of more than 40 %. Major contributors responsible for this

increase are wood (biomass) for the production of electricity and solar-thermal

energy for the production of hot water in the residential sector.

In essence, a PEC target corresponds to an energy-efficiency target. This energy-

efficiency target also has an influence on the use of renewable energies, as can be

seen by looking at column four. The PEC consumption target of 3.5 kW/Cap

arguments only marginal renewable-energy increases compared to the year 2000.

While we still observe a relatively small increase in the use of solar-thermal energy

and hydro power, all other renewable energy technologies cannot gain any shares.

The combination of strong kW/Cap targets and strong CO2 target fosters the

utilization of renewable energy, especially wood. More than 45 % of PE has a

renewable-energy origin. Therefore we identify a significant correlation between the

use of renewable energies and CO2 targets and virtually no correlation between the

use of renewable energies and PEC targets.

0

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Year 2000 Year 2050 Year 2050 Year 2050 Year 2050

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OtherWindWasteWoodSolar ThermalHydro Power

Energy carriers:

Figure 49: Primary energy consumption [PJ] of renewable energy technologies for various CO2 and kW/Cap

limits and an oil price of 75 US$2000/bbl.


As identified in the previous figure, wood (biomass) technologies are the major new-

renewable-energy source. Hydropower by far still has the largest renewable shares

but wood is the renewable energy fuel, which registers the largest increases.

Figure 50 shows the PE consumption of biomass from 2000 to 2050 for an oil price of

75 US$2000/bbl, a 3.5 kW/Cap as well as a 10 % CO2 reduction target. The figure

shows two peaks for the use of wood, the first in 2015 and the second in 2050.

According to the scenario assumption, in 2010 the Kyoto target (a CO2 reduction of

10 % compared to 1990) must be met. This target can only be met with a drastic

increase in the use of biomass to mainly satisfy the increasing electricity demand. A

CO2 compensation in other sectors, such as the residential or transportation sector,

are theoretically also possible but imply a too significant and too expensive

replacement of already exiting technologies in a short period of time. After the peak

consumption in 2015, the wood consumption declines because of investments in

more cost-effective and more efficient technologies to satisfy the constantly

increasing CO2 reduction. A transition time until 2025 is sufficient for investments in

less CO2 consuming technologies available at lower costs. Towards the middle of the

century the wood consumption peaks again due to the magnitude of CO2 reduction of

10 % per decade. In 2050, the full wood potential in Switzerland is used.

0

20

40

60

80

100

120

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pri

mary

-En

erg

y C

on

su

mp

tio

n [

PJ]

Combustion

Room and Building Heating: Chimeny, stove, oven

Room and Building Heating: Pellet

Other Uses

Technologicaluses:

Figure 50: Primary energy consumption [PJ] of wood technologies for an oil price of 75 US$2000/bbl. A 3.5

kW/Cap target and 10 % CO2 reduction are applied.


Cost analysis

The cost analysis in MAKRAL type of model is based on total-system costs.[91]

Total-system costs refer to the discounted sum of the annual costs minus revenues.

In a simplified way, they are calculated as follows:

Investment costs

+ Costs for sunk material during construction time

+ Variable costs

+ Fix operating and maintenance costs

+ Surveillance costs

+ Decommissioning costs

+ Taxes

- Subsidies

- Recuperation of sunk material

- Salvage value

0

5

10

15

20

25

30

35

40

45

50

5.2 kW (NoLimit)

4.9 kW (NoLimit)

4.8 kW (NoLimit)

3.5 kW target 3.5 kW target 3.5 kW target

No CO2 limit CO2 reductionof 5 % per

decade

CO2 reductionof 10 % per

decade


decade


decade

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$

20

00]

Figure 51: Total-system-costs increase for an Oil Price of 75US$2000/bbl.

In the context of this analysis we show the additional total system-costs. Additional

because the costs shown here refer to cost increases of each specifically constrained

scenario (CO2 or kW/Cap) compared to a reference case. The reference case


represents the non (CO2 or kW/Cap) constrained scenario at a specific oil price.

Figure 51 shows the total-system cost increases for various scenarios at an oil price

of 75 US$2000/bbl in 2050. The figure is separated into two parts. The columns on the

left hand side show costs of the reference case and CO2 constrained scenarios. The

columns on the right hand side show costs of 3.5 kW/Cap constrained scenarios in

combination with various CO2 targets.

Obviously structural changes of the energy system cost large amounts of money. A

CO2 reduction of 5 % per decade involves costs of more than 15 billion US$2000. To

achieve more ambitious CO2 targets result in a cost increase of nearly 25 billion

US$2000. The same cost-increase effects can be also observed at higher oil prices,

see appendix 5.4. However, for high oil prices more stringent CO2 targets can be

obtained at lower cost. More efficient (less CO2 consuming technologies) already

become competitive in the reference case without any specified CO2 target. For

instance at an oil price of 125 US$2000/bbl, the costs to achieve a 10 % reduction

amount to 16 billion US$2000.

Scenarios with combined CO2 and kW/Cap also show similar price increases but at a

higher cost level. The combined scenario with a 5 % CO2 reduction has higher costs

than the 10 % CO2 reduction of without any kW/Cap targets. Moreover to reach very

high CO2 targets in combination with a 3.5 kW/Cap target rises the costs in total to 40

billion US$2000. Moreover, note also that the combined 3.5 kW/Cap and 10 % CO2

reduction scenario costs less than the two signal constraint scenarios 3.5 kW/Cap

and 10 % CO2 added up - about 43 billion US$2000. This difference is an indicator for

technological synergies of combined-targets scenarios.

When does Switzerland have to take action to achieve specific (political) targets?

The answer to the question largely depends on the type of target. According to our

definition of the CO2 limits, Switzerland has to meet her voluntarily Kyoto

commitments in 2010.[92] Therefore, strict CO2 targets require taking action as soon

as possible, which is reflected by high cost increases at the same time, see Figure

52. Surprisingly, these large investments pay out towards the middle of the century

having even smaller costs than the reference case. On the contrary, a long term

target such as the 3.5 kW/Cap society requires major investments towards the

middle of the century. As mentioned above, the combined CO2 and kW/Cap

scenarios are the most expensive ones. Moreover, in order to reach these targets

high investments are necessary in virtually all time periods.


-5

0

5

10

15

20

25

30

35

40

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

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al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$

20

00]

No kW/Cap target and 10 % CO2 limit 3.5 kW/Cap target and no CO2 limit 3.5 kW/Cap target and 10 % CO2 limit

Figure 52: Annual total-system-costs increase for an oil price of 75US$2000/bbl.

4.5 Conclusions

The vision of a 2000-Watt society should be seen as a long-term goal. During the first

half of the century only intermediate steps towards the 2000-Watt society can be

achieved. The analysis shows that until 2050, a 3500-Watt society can be reached at

maximum. Even this intermediate step is associated with a considerable

transformation of the Swiss energy system. The major transformation concerns

energy-transformation and energy-demand technologies. With regards to energy-

transformation technology the issue arises whether Switzerland should invest in

nuclear energy or high-efficient gas-fired CHP plants. By merely looking at the PEC

consumption target, CHP plants are favoured with the burden of increase of CO2

emissions. With regards to energy-demand technologies drastic transformation are

required.

In detail we investigated transformation changes in two end-use sectors, the

residential and transportation sector. The residential sector has the largest energy

reduction potential. The total FE consumption of this sector could reduce to about

100 PJ in 2050. At an oil price of 75 US$2000/bbl, this implies a reduction of 45 %.

Major energy reductions are achieved in the RH sub-sector. Although this sub-sector

remains to be the main consumer by looking at the consumption shares in 2050, RH


consumes only 43 PJ. This is only possible because of major investments in energy

saving measures as well as fuel and technology switches to heat pumps and district

heating systems. The transportation sector has a smaller but still remarkable energy

reduction potential of 20 % in 2050. Passenger cars, which remain to be the largest

consumers, undergo a sustainable fuel and technology transformation as well. While

this sub-sector consumes more than 160 PJ FE in 2000, the consumption is reduced

to around 110 PJ in 2050. Natural gas and diesel hybrid as well as high-efficient

diesel ICE cars would be the technological choice of the future. Additionally,

hydrogen cars would have an initial market penetration.

Supporting a 3500-Watt society is an energy-efficiency target. This energy-efficiency

target has restrictions in connection with CO2 emissions reductions. A 3500-Watt

society reduces CO2 emissions by nearly (little less than) 5 % per decade. More

stringent emission reductions require the formulation of extra CO2 goals. Because of

this reason, we investigated combined scenarios on CO2 emissions and PEC

consumption in more detail. These scenarios show that, as the constraints on PEC

consumption and CO2 emissions become more stringent, the contribution of nuclear

and renewable energy become increasingly indispensable. Additionally, investments

into high-efficient and at the same time less CO2 consuming end-use technologies

are necessary relatively soon from now. Such technologies are for instance fuel cells

and solar-water heaters as well as excellent energy-saving measures.

The transformation of the energy system is not cost-free. The additional costs to

reach a 3500-Watt society, including CO2 targets, amounts to 20 to 40 billion

US$2000. If the main reason to reach a 3500-Watt society was CO2 reduction, then the

target is be questionable. The costs to reach significant CO2 reductions (but

excluding a PEC constraint) are with 15 to 25 billion US$2000 much cheaper.

Switzerland has a multiple choice of future pathways. Depending on the target

behind a political decision, each choice must be evaluated thoroughly. However, if

the target is to aim at high CO2 reduction, investments into clean technologies must

be made rather sooner than later.

Complementary analyses 92

5 Complementary analyses

Although each policy instrument studied so far has been tested using a sensitivity

analysis, a more extensive parametric analysis can provide insights into the

robustness of the results. This is particularly important for key parameters that can

significantly influence outcome of the model. Nevertheless, despite the fact that a full

and comprehensive parametric analysis was beyond the scope of this thesis, a

sensitivity study on the impacts of discount rates (dr) is analysed here. This analysis

is done in section 5.1.

The future costs of hydrogen fuel-cell cars are uncertain. The retail price of fuel-cells

largely depends on the price of the fuel cells and their stack size. Therefore, we

reassessed the passenger cars sector and especially the penetration of hydrogen

fuel-cell cars using optimistic assumptions. This is done in section 5.2.

The primary-energy content of most renewable energies can be defined in several

ways and varies depending on the particular statistic. To overcome this dilemma, we

investigated different energy-conversion equivalents for renewable energies. This

analysis is done in section 5.3.

The objective of the modelling approach so far was to find a least-cost solution by

minimising the total system costs and to satisfy exogenously specified levels of

energy-service demands. However, if the demands are inelastic, the model cannot

capture the consumer’s price-induced feedbacks. From an all-embracing policy-

making point of view it is desirable that the modelling framework captures both the

flows and prices of energy commodities such that the amount of energy service

demanded corresponds to the money the consumer would be willing to pay.[93] In a

MARKAL-class model a feedback between prices and demand can be evaluated by

a partial-equilibrium analysis with elastic demands. This analysis is done in section

5.4.

In future, new biomass technologies can gain significant importance in the Swiss

energy sector. The conversion of biomass into high quality, flexible final-energy

carriers constitutes a convenient vehicle to add value to wood as an energy resource.

As a result of its neutral CO2 emissions, biomass-based energy carriers can

contribute to substitute carbon-intensive fossil fuels in the energy markets. At the

same time, greenhouse gas emissions can be reduced and benefits in terms of

security of energy supply can be achieved. Therefore, we assess the economic


conditions under which new biomass technologies become competitive. The focus of

this assessment is on the production of synthetic natural gas (bio-SNG) from wood in

a methanation plant. This analysis is done in section 5.5.

5.1 Sensitivity analysis on discount rates

For long-term policy making the choice of discount rate (dr) determines the present

value of these policy-induced costs (or benefits). In addition, a low dr decreases

annualized payments of investments and therefore favours capital-intensive

investments. Given the controversial issues about dr [94], we scrutinize a low dr of 3

% and a high dr of 5 %. The discount rate of 3 % is also used in the baseline

scenario. Note that MARKAL class models define two types of dr, DISCOUNT and

DISCRATE. DISCOUNT refers to the overall long-term dr for the whole economy and

must be defined for all scenarios. It is mainly used to report the discounted costs

(e.g. total system costs) to the base year. DISCRATE is associated with an individual

technology (or all technologies in a sector) and is manly used for the calculation of

the Capital Recovery Factor (CRF)55 to determine the annual payments for

investments.[96] The low and high dr values are used for both model parameters.

0.0

1.0

2.0

3.0

4.0

5.0

6.0

dr 5 % dr 3 % dr 5 % dr 3 %




Pri

mary

En

erg

y C

on

su

mp

tio

n [

kW

/Cap

ita]

RenewablesHydroNuclearNatural GasOilCoal

Energycarriers:

Figure 53: Primary energy per capita [kW/Cap] consumption for an oil price of 75 US$2000/bbl with discount

rates (dr) of 3 and 5 % as well as no kW/Cap target and a 3.5 kW/Cap target.

55 The CRF is the ratio of a constant annuity to the present value of receiving that annuity for a given length of time.[95]


Figure 53 illustrates the PE consumption of non kW/Cap constrained scenarios on

the left-hand side and of 3.5 kW/Cap constraint scenarios on the right-hand side. The

non-constrained scenarios show a relatively small but notable difference in the PE

consumption. By decreasing the dr from 5 to 3 % the PE consumption reduces by

little more than 3 %. At the same time the amount of oil and gas consumed in 2050 is

less due to investments in more capital-intensive and energy-efficient technologies.

In turn, the total CO2 emissions reduce by 7 % (from 40.3 to 37.7 Mt). On the

contrary the 3.5 kW/Cap constraint scenarios show in essence no difference in total

PE consumption. This effect is nicely reflected by the CO2 emissions in 2050. The

emissions differ by less than 0.3%. A strong kW/Cap constraint already demands

such capital-intensive technologies that a low dr does not show any effect.

We conclude that the dr changes have only little effect on the PE consumption,

hence on future-investment choices in Switzerland. This statement becomes even

more valid for strong kW/Cap (and CO2 targets). 3.5 kW/Cap scenarios have the

same PE consumption shares in 2050, independent of the dr used.

5.2 The influence of fuel-cells price and stack sizes on hydrogen

cars

The retail price of fuel-cells largely depends on the price of the fuel cells and their

stack size. Considering the uncertainties in fuel-cell prizes and the variety of stack

sizes, we analysed two different fuel-cell prices and stack sizes for hydrogen-driven

passenger cars. In the baseline scenario, we assumed a fuel-cell price of around 700

US$2000/kW (600 €2003/kW) in 2010, which reduces to around 115 US$2000/bbl (100

€2003/kW) until 2050.[97,98] The stack size is 80 kW. For the sensitivity run, we

assumed that the price reduces by half as well as a stack size of 50 kW. Additionally,

for the sensitivity run we assumed a PEC target of 3.5 kW/Cap and a CO2 reduction

of 10 % per decade.

The results of the baseline run are elaborated in section 4.4 in detail. In the beginning

of the century, we observed a domination of gasoline and partially diesel fuelled

internal-combustion-engines (ICE) cars. This domination declined over time,

gasoline-fuelled cars reduced to marginal amounts and ICE engines were replaced

by the hybrid technology. Hybrid diesel and hybrid natural gas cars had the largest

market shares in 2050. However, although hydrogen cars started to penetrate in

2045, this penetration remained at rather marginal levels. On the contrary, when fuel-


cells can be produced at lower costs the penetration of hydrogen cars increases.

This effect is supported by installing smaller-sized engines in light-vehicle passenger

cars, see Figure 54. Hydrogen fuel-cell cars reach readiness of marketing already in

the year 2030. In 2050, hydrogen fuel-cell cars could have a share of up to 21%

under these assumptions.

0

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40

60

80

100

120

140

160

180

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

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on

su

mp

tio

n [

PJ]

H2 Hybrid Fuel CellH2 Fuel CellH2 HybridNatural Gas HybridNatural GasGasoline HybridGasoline ICEDiesel HybridDiesel ICE

Engine drives:

Figure 54: Final-energy consumption of passenger cars at an oil price of 75US2000/bbl, 3.5 kW/Cap primary

energy and a CO2 reduction constraint of 10 % per decade. Fuel stack price is assumed to be 300US$/kW in

2010 and the size of one fuel cell is 50 kW.

We can summarize that the market penetration and the readiness for marketing of

hydrogen fuel-cell cars largely depends on the price of fuel cells and the size

installed in each car. If it is possible to produce light-vehicles at low costs, hydrogen

cars could reach significant market shares in the second quarter of the 21st century.

5.3 The influence of renewable energy-conversion equivalents on

the production of electricity

Primary energy is defined as the energy content of an energy carrier, which has not

been transformed by any means. This definition causes a dilemma when looking at

renewable energies. Most renewable energies such as wind, photovoltaic or

hydropower are characterized by a substantial difference compared to all other fossil

energy carriers (biomass being the only exception). While fossil energy carriers and


biomass have specific (measureable) energy contents, e.g. [MJ/toncoal] or [MJ/m3Gas],

other renewable energies are characterised by energy flows, e.g. wind velocity [m/s]

(Pwind ~ v3 [99]) or solar radiation [kW/m2] (Psolar = 1.366 kW/m2 [100]). Therefore, to

be mathematically correct, the primary-energy use of fossil energy carriers can not

be added to the primary-energy use of renewable energy.

To overcome this dilemma, primary-to-final energy-conversion equivalents are

introduced for statistical purposes. These equivalents could for instance relate to the

technical efficiency or to fossil or other equivalents56. The 2004 Swiss renewable

energy statistics still defined various conversion factors for different renewable

energy technologies (e.g. hydropower 80 %, photovoltaic 11 % and wind 41 %).[102]

The 2005 Swiss renewable energy statistics have been changed to IEA regulation

using an energy-conversion equivalent to 100 % for renewable energy technologies

[59,103]. So far, in SMM, we have used the fossil equivalent for renewable energy

technologies according to the standard MARKAL conversions.[101] Only for hydro

power we used the conversion equivalent of 80 % according to the older SOFE

accounting scheme.

Because of various possible energy-conversion equivalents, which could be used for

an analysis, in this section we studied the effects of a renewable energy-conversion

equivalent of 100 % (including hydro power and excluding biomass) and compared

the results to our previous scenarios. An energy-conversion equivalent of 100 %

implies that the final use of energy is equivalent to the primary use of energy. The

new scenario results are labeled ‘100 eq.’, while the previous results are labeled

‘fossil eq.’ and are shown in Figure 55.

The figure depicts the production of electricity, comparing three scenario sets. The

first set, depicted by the first two columns on the left-hand side, refers to a 10 % CO2

reduction per decade limit. The second set, the two columns in the middle, reflects

the 3.5 kW/Cap target. The third set, the two columns on the right-hand side, shows

combined CO2 reduction and kW/Cap targets. In all scenarios the demanded

electricity and therefore the choice of technologies in the end-use sectors remain

similar. The total production of electricity alters only by small amounts. The significant

difference is the choice of electricity-production technologies to satisfy the demand

for electricity.

56 The fossil-fuel equivalent for non-fossil sources is taken as the reciprocal of the average efficiency of the fossil fuel power plants, and is used for reporting the primary-energy equivalent of renewable and nuclear energy production of electricity.[101]


In the first scenario set, switching from the fossil-equivalent scenario to the 100 %

equivalent scenario decreases the attractiveness of biomass technologies in favour

of wind turbines. In the second set, we observe a strong decrease in natural gas

thermal production, which is replaced by solar and wind technologies. In the third

scenario set both natural gas thermal and biomass are substituted by solar and wind

technologies. Additionally, remarkable is the penetration of nuclear energy in this

scenario set.

0

10

20

30

40

50

60

70

80

90

No kW/Captarget

No kW/Captarget

3.5 kW/Captarget

3.5 kW/Captarget

3.5 kW/Captarget

3.5 kW/Captarget

10 % CO2 red. 10 % CO2 red. No CO2 limit No CO2 limit 10 % CO2 red. 10 % CO2 red.

fossil eq. 100% eq. fossil eq. 100% eq. fossil eq. 100% eq.

Ele

ctr

icit

y P

rod

ucti

on

[T

Wh

]

Solar Power

WindTurbinesBiomass CHP

Natural GasCHPThermalCogenerationBiomassThermalNatural GasThermalNuclearPowerHydro Power


Figure 55: Electricity production for a fossil equivalent and a 100% conversion equivalent of renewable energy

technologies (expect for biomass technologies) at an oil price of 75US2000/bb in 2050. Various scenarios

compare combinations of a 3.5 kW/Cap primary energy and a CO2 reduction constraint of 10 % per decade.

The effect of switching from biomass and natural gas thermal technologies to solar

and wind technologies directly relates to the higher energy-conversion equivalent of

100 % compared to the fossil equivalent of 33 %. The 100 % equivalent clearly

argues in favour of the competitiveness of renewable energies. Fossil but also

biomass technologies, with much lower efficiencies than 100 %, are disadvantaged.

This is particularly illustrative in the second scenario set, i.e. the 3.5 kW/Cap

scenarios.

The third scenario set, where both CO2 and the kW/Cap targets have to be fulfilled at

the same time, shows an additional effect. In the previous two scenario sets either

biomass or natural gas was replaced. In the third set both technologies are replaced


with renewable energy technologies, both having 100 % energy-conversions

equivalents. Hence, for the same amount of final-energy less primary energy is

consumed (note that also the energy-conversion equivalent for hydro was increased

from 80 to 100 % as well). In turn this gives space for nuclear energy with a relative

low energy-conversion equivalent of 33 %. Nuclear energy is also favoured by the

strong CO2 target of 10 % per decade.

5.4 Partial equilibrium with elastic demands

A partial equilibrium MARKAL model with elastic demands adopts a concept where

end-use demands are not fixed but elastic to their own prices. The equation below

illustrates this characteristic. D0 and P0 refer to Demands and Prices in an initial

scenario without elastic demands (the demands are exogenously defined). For a

given price elasticity, the demand Dt can be reduced when the corresponding price Pt

increases (scenario with elastic demands). Thereby the elasticity reflects the

relationship between changes in quantity of a good demanded and changes in its

price. In Swiss-MARKAL, we assume an elasticity of 0.3 for all demands.[104]

Figure 56: Partial equilibrium model with elastic demands (based on [101,104]).

α

��

��

�=��

�

��

�

tt P

P

D

D 00


D: Demand

P: Price

α : Elasiticity

Index 0: Initial Scenario without elastic demands

Index t: Scenario with elastic demands

This relationship can be also explained using Figure 56 illustrating the price and

quantity (demand) relationship in a simplified manner. The initial equilibrium point Eq0

reflects the optimal solution of an initial scenario without elastic demands. In the

scenario with elastic demands the model can chose any (base on the elasticity)

solution on the demand curve by reducing the quantity (demand for a good). As a

result we obtain a new equilibrium point Eqt with the consumer surplus (B) and the

producer surplus (A). Note that the Swiss-MARKAL model with elastic demands does

not capture the entire macroeconomic feedback associated with the applied energy-

policy instruments. This would require coupling of the model to a macro-economic

model, (e.g., the MACRO module).[105] More information can be found in [93,104].

Figure 57 shows the PEC consumption of three scenarios with and without elastic

demands for an oil price of 75 US$2000/bbl in 2050. The first column on the left shows

the PEC without elastic demands. As illustrated in Figure 27, in this scenario

Switzerland mainly depends on fossil (natural gas and oil) fuels and hydro power.

Evaluating the same scenario using an elastic demand approach (centre column), we

attain different PEC consumption shares. The amount of fossil fuels reduces from

67 % to 53 %. Remarkable is also the utilization of nuclear energy with a share of

16 %.

How can this change in the PEC consumption be explained? We firstly take a look at

the demand reduction in the end-use markets. Exemplarily choose the residential

heating (RH) and passenger car sectors. The demand reduction in the RH sector

adds up to 8 % – 14 % compared to the demand in scenario without elastic

demands. Thereby MFH reduce demand by 12 % - 14 % and SFH by 8 % - 10 %.

The demand reduction in the passenger cars sector adds up to 7 %. These

reductions lead to a lower consumption of fossil fuels, which is reflected in the PEC

balance. Secondly, the demand reduction and consequently the consumption of less

fossil fuels open the possibility for the production of energy with lower-efficient


technologies. Note that the total PEC consumption is limited in all scenarios.

Therefore, instead of producing electricity by high-efficient gas power stations,

electricity is produced by less efficient but also less costly nuclear power stations.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

3.5 kW/Cap target 3.5 kW/Cap target 3.0 kW/Cap target

no elastic demands elastic demands elastic demands

Pri

mary

En

erg

y [

kW

/Cap

ita]

Other RenewablesHydroNuclearNatural GasOilCoal

Energy carriers:

Figure 57: Primary energy per capita [kW/Cap] consumption for an oil price of 75 US$2000/bbl with and with

elastic demand calculations.

A second issue of interest would be to define the maximum possible PEC reduction

taking into consideration specific price elasticities and resulting demand reductions.

Obviously, although the demand for energy reduces due to high energy prices, there

is still a limit to the possible demand reduction. This limit and the corresponding PEC

fuel shares are illustrated by the third column in the figure. At maximum, we can

reduce the PEC consumption to 3 kW/Cap. The PEC consumption cannot be

reduced any further by 205057. The 3 kW/Cap target can be obtained by reducing

additional demand for electricity, which in turn lowers the PEC consumption of

nuclear energy and natural gas. However, note that even by achieving a 3 kW/Cap

using elastic demands, new investment in nuclear power station or the extension of

their decommissioning time are favourable.

57 In the analysis we lowered the PEC consumption target step wise by 0.5 kW/Cap. A PEC consumption of 2.5 is not feasible.


5.5 Assessing wood-based synthetic-fuel technologies

In future, new biomass technologies can gain significant importance in the Swiss

energy sector. Therefore, this section assesses the economic conditions under which

new biomass technologies become competitive. The focus of this assessment is on

the production of synthetic natural gas (bio-SNG) from wood in a methanation plant.

In addition to a reference scenario, the effects of increasing oil and gas prices, the

effects of allocating subsidies to the methanation plant and the effects of competition

between the methanation plant and a biomass-based Fischer-Tropsch (FT) synthesis

are evaluated. An additional sensitivity analysis is performed by varying investment

costs of the methanation plant. Note that this section of the dissertation was

conducted with an older version of the Swiss-MARKAL model, status January 2005.

The main difference between the latest version and the version January 2005 is the

absence of energy-saving option in the residential heating sector. However, the

scope of the thesis did not allow a new analysis with the latest version of the model.

For this assessment, each wood-based energy process is embedded in a process

chain that is linked to the energy production, transmission and distribution (T&D)

systems of Switzerland. Figure 58 to Figure 60 depict three types of biomass-process

chains examined in this paper. The first type includes processes that produce fuels

for the transportation sector, namely bio-SNG and FT liquids (Figure 58). The second

type includes processes related to combined heat and power (CHP) production from

wood (Figure 59). The third type includes technologies that use wood to produce

heat only (Figure 60). The technological data description is attached in appendix 3.

Methanation

Fischer-TropschSynthesis

Natural Gas T&D

DieselT&D

CNG ICE Car

Diesel ICE Car

Wood Chips

Figure 58: Wood-based process chains for bio-fuel production from wood considered in the SWISS-MARKAL

model. CNG stands for compressed natural gas and ICE stands for internal combustion engine.


Wood Chips

Methanation

Wood CHP (<2 MW)Gasification

Wood CHP (<2 MW)Combustion

Wood CHP (>2 MW)Gasification

Wood CHP (>2 MW)Combustion

Natural Gas Distributed CHP

Short-DistanceDistrict Heating

Long-DistanceDistrict Heating

Electricity

Heat

Electricity

Electricity

Electricity

Heat

Heat


Electricity

Figure 59: Wood-based process chains for combined heat and power (CHP) production considered in the

SWISS-MARKAL model. For simplicity, transmission and distribution processes are not shown in the diagram.

Wood Chips

Methanation

Wood Chip Heating (50 kW)

Wood Pellets Production



Co-Combustion in Gas Turbine


Heat

Gas HeatingSFH

Heat

Wood Pellet HeatingSFH

Heat PumpSFH

Heat

Heat

Figure 60: Wood-based process chains for heat production considered in the SWISS-MARKAL model. The

abbreviation SFH stands for Single Family Houses. For simplicity, transmission and distribution processes are

not shown in the diagram.


As mentioned above, a special attention is given to the wood-methanation

technology to produce bio-SNG and the FT synthesis to produce FT liquids, some of

which can be used in the same way as conventional diesel.[106,107] The specific

costs of the methanation plant and FT synthesis technologies, especially the

investment costs, strongly depend on the size of the plant. In this assessment the

costs of the methanation plant are based on a plant size of 100 MW, whereas the

costs of the FT synthesis are based on a plant size of 400 MW. Because of the

differences in the economies of scale, the specific investment costs of the FT plant

are slightly lower than those of the methanation plant. This in turn directly influences

the generation costs of the energy carrier produced. Since Switzerland is a small

country, we consider a 400 MW FT plant not as appropriate for Switzerland, but we

include the FT facility to test the competitiveness in respect to the methanation plant

in a separate section (section 5.5.4).

5.5.1 Oil price sensitivity analysis

Future oil prices are uncertain and difficult to predict.[108,109] Therefore, the price

levels chosen in the scenarios analyzed here are illustrative and do not represent the

endorsement of any particular oil price projection by the authors. Figure 61 shows the

market share (primary energy use) of wood-based energy-technologies when oil and

gas prices increase. In our scenarios the oil prices increase linearly from 28

US$2000/bbl in 2000 to 100 US$2000/bbl, 110 US$2000/bbl, 120 US$2000/bbl and 130

US$2000/bbl in the year 2050 (OIL100 to OIL130 represents the oil prices 100

US$2000/bbl to 130 US$2000/bbl in 2050). The figure displays the primary-energy use

of wood for the final year of the modelling horizon, 2050. The methanation plant

produces heat with an efficiency of 10 % and bio-SNG with an efficiency of 55 %. In

relation to that, the results indicate how much wood is used for the production of heat

and bio-SNG. The figure also shows in which sectors the produced bio-SNG is used.


0

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OIL 100 OIL 110 OIL 120 OIL 130

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Methanation Plant (bio-SNG: Transportation Sector)Methanation Plant (bio-SNG: Residential Sector)Methanation Plant (Heat: All Sectors)Wood CHP (>2 MWel) Gasification

Biomass technologies:

Figure 61: Primary-energy use of wood by different technologies for oil prices between 100 and 130 US$2000/bbl

in the year 2050. The Fischer-Tropsch synthesis is not included as an option.

Figure 61 labels the use of biomass by current technology standards as conventional

technologies. In the year 2000, conventional technologies use biomass of 20 PJ (or

about 20 % of the total theoretical wood potential) in Switzerland.58 In our analysis

these conventional technologies are limited by an upper ceiling of 20 PJ, i.e. as in the

current use of wood. Hence, in this part of the analysis the technologies under

investigation (Figure 58 to Figure 60) compete for the remaining amount of wood,

which adds up to at least 80 PJ.

In Scenario OIL 100, where the oil price reaches 100 US$2000/bbl in the year 2050,

only the production of heat and electricity in a Combined Heat and Power (CHP)

biomass plants is competitive in Switzerland. The first large (more than 2 MW) CHP

gasification plant will be built in 2040. Thereafter the amount of wood converted to

electricity and heat increases to about 6 PJ in 2050 (about 6 % of the total wood

potential of Switzerland). In this scenario, neither the methanation plant nor any other

biomass technology under investigation has the potential to penetrate the market.

In the scenario OIL 110, the amount of wood used in CHP plants is much higher than

in the previous case (about 25 PJ). The first investment will be made in the year

58 In the year 2000, the use of wood can be separated into single room heating systems (27 % of the total), building heating systems (25 %), automatic firing (38 %) and special firing (9%).[48,110]


2030. Additionally to the CHP plant, the methanation plant becomes competitive. It

should convert a total of 1.5 PJ wood into bio-SNG and heat carriers in 2050. In this

case, wood is converted in the methanation plant into bio-SNG, which is used in the

residential sector.

In scenario OIL 120, four distinct effects take place. Firstly, CHP plants already start

to be competitive in 2025 and methanation plants become competitive as of 2045.

Secondly, the amount of wood converted in CHP plants to heat and electricity

increases from 25 to about 29 US$/PJ. Thirdly, methanation plants increase their

competitiveness on the Swiss market. By the year 2050, about 40 PJ of wood are

converted to bio-SNG and heat. This time by far the largest share of bio-SNG is used

in the transportation sector. Fourthly, the residential sector cannot solidify its

importance. Moreover, if the oil price increases further to 130 US$2000/bbl in the year

2050, the trends outlined in scenario OIL120 are in general terms confirmed.

The results of the analysis suggest that methanation plants may become competitive

at high prices of oil. Thus, provided that oil reaches a threshold price, favourable

market conditions may appear for methanation plants to successfully penetrate the

market. The threshold price of oil corresponds to the year in which the methanation

plants start to penetrate the market and to the value of oil price at that year. This

threshold is around the value of 110 US$2000/bbl. Hence, the results from this part of

the analysis indicate that if the oil price reaches 110 US$2000/bbl or more, the

methanation plants will be competitive enough to penetrate the market. However, if

the oil price is below the threshold of 110 US$2000/bbl, the methanation plants would

require supporting policy measures to enter the market.

Figure 62 shows the final-energy consumption by fuel in the transportation sector in

the year 2050. We identify a clear shift from oil products to natural gas and bio-SNG.

Oil products dominate the final-energy mix in the transportation sector in the baseline

scenario and virtually no gaseous energy carriers (natural gas or bio-SNG) are

consumed. In the scenarios OIL100 to OIL130, this has changed significantly. The

share of natural gas and bio-SNG increased to about 19 to 37 %, depending on the

scenario.59 Generally speaking, under the assumption of increasing oil and gas

prices, natural gas substantially increases its role in the transportation sector. With a

high increase in oil and natural-gas prices in scenarios OIL120 to OIL130, a fraction

59 The increasing participation of natural gas and bio-SNG at the final-energy level is mainly driven by the introduction of gas-powered cars in the passenger car sub-sector. For an analysis of the conditions under which gas-powered vehicles can penetrate the Swiss market, see [111].


of this natural gas is replaced by bio-SNG. In the scenario OIL120 and OIL130, 5 %

and 9 % of the gas transported in gas pipelines is bio-SNG.

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Basecase OIL 100 OIL 110 OIL 120 OIL 130

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bio-SNGNatural GasElectricityFT-DieselDieselGasolineAvi. Gasoline

Energycarriers:

Figure 62: Final-energy consumption by fuel of the transport sector for oil prices between 100 and 130

US$2000/bbl in the year 2050.

On average in the above described scenarios, the emissions are about 40.5 Mt CO2

or 16 % lower than the emissions in the baseline scenario (oil price of 50 US$2000/bbl

in 2000). The reduction is influenced by two factors, namely fuel switching to cleaner

fuels and investments in more efficient technologies. In total, the reduction amounts

to 3.2 %, 6.3 %, 8.7 % and 9.3 % for the scenarios OIL100, OIL110, OIL120 and

OIL130. A switch away from oil and gas production to electricity and heat is

identified.

These results illustrate the potential synergies that can exist between bio-SNG and

natural gas. Specifically, the development of an infrastructure for transmission and

distribution of natural gas and the promotion of gas-based technologies in the

transportation sector can be beneficial for the introduction of bio-SNG. In its turn, bio-

SNG can contribute to a hedging strategy against substantial oil and gas-price

increases and to “greening” of natural gas by reducing CO2 emissions.


5.5.2 Oil price and subsidy sensitivity analysis of the methanation

plant

In this section we analyse various subsidy levels to investigate an earlier market

penetration of the methanation plant at less drastic increases in the fossil resource

prices. Thereby, the focus is only on the penetration of the methanation plant – all

other biomass technologies are not analysed in detail in this section. Figure 63

shows the result of this analysis. The three-dimensional graph shows the crude oil

price in [US$/bbl] in the year 2050 on the x-axis, the level of subsidy in [US$/GJ] on

the y-axis and the primary-energy consumption of biomass for the methanation plant

in [PJ] on the z-axis. The primary consumption of biomass is the indicator for the

competitiveness of the methanation plant. The graph can be read starting from the

point representing an oil price of 50 US$2000/bbl and a subsidy level of 0 US$2000/GJ.

This point represents the baseline described in the previous section. Starting from

this point we could move along the x-axis and reach higher oil price keeping the

subsidy level constant at 0 US$/GJ. At an oil price of 110 US$2000/bbl we observe a

first market penetration of the methanation plant. Increasing the oil price further

results in a higher biomass consumption. In other words, the competitiveness of the

methanation plant increases.

Additionally, we could keep the oil price constant at 50 US$2000/bbl and increase the

subsidy level, going along the y-axis, or we could choose any in-between scenario

selecting a specific oil price and a specific level of subsidy. At an oil price of 50

US$2000/bbl, the subsidy needs to reach 6 US$2000/GJ (3.24 Rp/kWh) for the

methanation plant to reach a competitive level. If, for example, the oil price is 80

US$2000/bbl in 2050, the subsidy level must be 3 US$2000/GJ. The competitiveness of

all in-between scenarios for various oil prices is indicated by the ‘Market Penetration

Threshold’-line in the figure. In other words, the ‘Market Penetration Threshold’

illustrates the oil price and the corresponding subsidies necessary for the

methanation plant to be an economically attractive investment option in the energy

sector. For all other combinations of oil prices and subsidy levels (e.g. 70 US$2000/bbl

and 2 US$2000/PJ) below the ‘Market Penetration Threshold’, the plant is not an

economically-viable option. The figure also shows an upper plain for very high oil

prices and subsidies. This plain indicates that the maximum potential of biomass is

used in Switzerland.


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130

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Primary Energy

Consumption [PJ]Biomass for Methanation

Subsidy

[US$2000/GJ]

Oil price in 2050

[US$2000/bbl]

Baseline

Market

Penetration

Threshold

Figure 63: Market penetration of the methanation plant for different oil prices and subsidies levels. The market

penetration in the figure corresponds to the use of biomass for the Methanation processes expressed in [PJ].

As proven in this section, the introduction of subsidies helps to foster the market

penetration of the methanation plant at oil prices below 110 US$2000/bbl. Such

subsidies directly support an earlier market penetration, while a carbon tax is an

indirect support for the market penetration of the methanation plant. In a simplified

form, the equation for the methanation plant to be competitive can be expressed as

Oil Price + Carbon Tax + Subsidies ≥ 110 US$2000/bbl.

5.5.3 Investment cost sensitivity analysis of the methanation plant

The robustness of the result obtained so far can be analysed by conducting a

sensitivity analysis on the investment costs for various oil prices. Figure 64 illustrates

the results of the sensitivity analysis. The three-dimensional graph depicts the

percent change of investment cost on the x-axis, the crude oil price in [US$2000/bbl] in

the year 2050 on the y-axis and the primary-energy consumption of biomass for the

methanation plant in [PJ] on the z-axis. The percent investment cost changes are

altered between -10 % and +10 % of the investment costs used for all other

scenarios. The figure also illustrates the starting point of the analysis: 0 % in

investment costs and an oil price of 110 US$2000/bbl. This starting point corresponds

to the same biomass consumption values shown in scenario OIL110 in Figure 61 and


where the ‘Market Penetration Threshold’ line crosses the ‘Oil Price’ axis in Figure

63.

105

0-5

-10100

105

110

115

120

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30

40

50

60

Primary Energy

Consumption [PJ] Biomass for Methanation

Changes of Investment Costs [%]

Oil Price

[US$2000/bbl]

Starting Point

Figure 64: Market penetration of the methanation plant for different investment cost (high, medium, low). The

market penetration in the figure corresponds to the use of biomass for the Methanation processes expressed in

[PJ].

The figure puts forwards the conclusion that changes in the oil price have a stronger

effect than changes in investments costs. The change in investment costs only

influences the results when the oil price is at 110 US$2000/bbl. On the one hand, at an

oil price of 110 US$2000/bbl in 2050, the consumption of biomass (hence the market

competitiveness) decreases when the investments cost become 5 % more

expensive. On the other hand, when the investment cost decrease by 5 %, the

consumption of biomass shows a large increase. For all other oil prices (100, 105,

115, 120 US$2000/bbl) the investment-cost changes investigated here have no impact

on the consumption of biomass. On the contrary, the oil-price changes in the year

2050 shows a differentiated result. When the oil price reaches 105 US$2000/bbl, we

do not observe any consumption of biomass, hence investment in the methanation

plant is not economical, independent of the changes in investment costs. However,

for an oil price of 115 US$2000/bbl, we see biomass consumption of about 40 PJ for all

assumed investment costs. Therefore, the threshold for the market penetration of the


methanation plant at around 110 US$2000/bbl is confirmed, independent of the

scrutinized investment-cost fluctuations.

5.5.4 The comparison of Fischer-Tropsch and methanation plants

In the last section we examined the competitiveness of the methanation plant and the

FT Synthesis. For this analysis we assumed more moderate changes in the oil-price

development and lower subsidies on methanation plants compared to the scenario

sets described in the sections above. For all scenarios an oil price of 80 US$2000/bbl

in the year 2050 and a bio-SNG subsidy level of 4 US$/GJ (2.16 Rp/kWh) is chosen.

Moreover, the analysis in this section also differs regarding the presence or absence

of the modality (single product or co-production) of the FT facility.

Figure 65 presents a summary of the primary-energy use of wood for the year 2050.

As can be seen, when no investments can be made in the FT synthesis, the results

clearly augment the production of bio-SNG. About 70 PJ of wood is converted to

energy in methanation plants and about 84 % of the produced bio-SNG is used in the

transportation sector. Bio-SNG in the transportation sector substitutes conventional-

fuel cars such as diesel and gasoline cars whereas the amount of gas-driven cars

increases proportionally. However, if investments in a FT facility are allowed and if

this facility can co-produce electricity, it becomes more competitive than the bio-SNG

plant60. It is important to note that this is only possible because the by-product

electricity is dispatched to the Swiss electrical grid and can be sold to consumers.

Electricity, compared to heat produced by the methanation plant, can be sold at

higher prices and therefore the choice of investment is in favour of the FT synthesis.

Because of the large amount of FT liquids, the amount of diesel cars in the

transportation sector increases and the share of conventional gasoline cars drops

significantly compared to the baseline scenario. Generally, these scenarios favour

the FT synthesis, but the competitiveness of the FT synthesis plant is strongly

dependent on the possibility of selling the co-product electricity and the creation of

the infrastructure for a 400 MW plant.

60 The subsidies on bio-SNG remain at 5 US$/GJ (2.7 Rp/kWh).


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without Fischer-Tropsch with Fischer-Tropsch with Fischer-Tropsch

as a co-production plant producing only FT diesel

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Fischer-Tropsch SynthesisMethanation Plant (bio-SNG: Transportation Sector)Methanation Plant (bio-SNG: Residential Sector)Methanation Plant (Heat: All Sectors)

Biomass technologies:

Figure 65: Primary-energy use of wood for an oil price of 80 US$2000/bbl in 2050 and bio-SNG subsidies of

4 US$/GJ.

5.5.5 Remarks on the methantion plant

The scenarios examined the influence of such key factors as increases in the price of

fossil fuels (oil and natural gas), introduction of subsidies for bio-SNG production and

selected combinations of these factors. The results of our research suggest that with

present cost estimates, bio-SNG is still not competitive when compared to currently

dominating energy-generation technologies. In order to allow for a successful market

penetration, cost reductions of methanation plants are required. Alternatively, high

prices of oil and natural gas as well as subsidies for methanation plants would enable

their introduction. The robustness of the results for the methanation plant was

scrutinized using a sensitivity analysis for the methanation plant investments costs

for various oil prices. Additionally we investigated the competition of methanation

plants with Fischer-Tropsch (FT) installations.

If no supporting policy measures are undertaken the oil price needs to reach about

110 US$2000/bbl for bio-SNG to be competitive with conventional fuels. Using the

sensitivity analysis for investment costs of the methanation plant confirms this result.

If oil is traded at 50 US$2000/bbl in 2050, a subsidy of 6 US$/GJ is necessary to

initialize a market penetration. Nonetheless, the most plausible scenario is reached


by a combination of increasing oil prices and subsidies promoting the market

penetration of bio-SNG. Thus, if the oil price reaches values around 80 US$2000/bbl in

2050 and subsidies of 3 to 4 US$/GJ support the market penetration of bio-SNG, the

fuel can have a significant impact on the Swiss energy system.

The results of our analysis also suggest that a potential and very promising market

for bio-SNG is the transportation sector. Unlike the residential sector where

numerous alternative cost-effective technologies are already present, the

transportation sector contains a vast market segment where bio-SNG technologies

can take the leading role. Up to 37 % of the total fuel for transportation could be

coming from a combination of natural gas and bio-SNG in 2050. At the same time,

this scenario also introduces more efficient vehicle technologies. Hence, the

synergetic use of natural gas and bio-SNG in the transportation sector can increase

significantly and reduce the total final-energy consumption in this sector.

The penetration of bio-SNG also depends on the competition with other alternative

wood-based energy-technologies. Our analysis suggests that a biomass-fired facility,

co-producing FT liquids and electricity, can be a more cost effective alternative than

a facility co-producing bio-SNG and heat (not considering the logistic, environmental

and public-acceptance issues that would be raised by a FT facility). The results of our

analysis highlight the importance of exploring additional co-production strategies for

bio-SNG, i.e. together with electricity.

Conclusions and recommendations 113

6 Conclusions and recommendations

The overall goal of the dissertation was the assessment of intermediate steps

towards the 2000-Watt society in Switzerland. The concept of a 2000-Watt society

aims at consuming not more than 2000 Watts per capita (2 kW/Cap) of primary

energy society. For the analysis the cost-optimization Swiss MARKAL model (SMM)

is used. This energy-system model provides a detailed representation of all energy

technologies and energy flows in Switzerland. In the course of the dissertation, the

author provides insights into four main questions:

1) How much can the primary-energy per capita (PEC) consumption be lowered

until 2050? We tried to find an upper reduction potential of the PEC consumption

until 2050.

2) What are the cost-optimal technical choices until 2050? Each contemplated

scenario suggests a set of technologies. In particular we analysed electricity-

generation technologies, residential-heating systems (including energy saving

measures) and the development of the Swiss car fleet.

3) Will energy-related CO2 emissions reduce substantially? The emissions

reductions are compared to specific targets of only reducing CO2 emissions as

well as combinations of PEC and CO2 reduction targets.

4) What are the costs of reducing PEC consumption? By subtracting costs of each

constrained scenario from the baseline scenario, we found the additional costs

associated with each scenario policy.

6.1 The 2000-Watt society: Results from the Swiss MARKAL

model

This section illustrates the results obtained from the modelling analysis. The four

main results can be summarized as follows:

1) The PEC consumption target of 2000 Watts per capita should be seen as a long-

term goal. During the first half of the century only intermediate steps towards the

2000-Watt society can be achieved (see section 6.1.1).

2) To achieve already intermediate steps requires a transformation of the energy

use as we know it today. Thereby, the generation of electricity plays a key role.

The contribution of nuclear energy and renewable energies is indispensable. In

the residential sector the use of heat pumps and investments in energy-saving


options will be necessary. In the transportation sector, hybrid diesel and natural

gas cars will initiate important structural changes (see section 6.1.2).

3) All PEC consumption targets until 2050 can reduce CO2 emissions to an

equivalent of 5 % per decade at maximum. Less strong PEC targets have even

higher emissions. For significant CO2-emission reductions, targets must be

formulated explicitly (see section 6.1.2).

4) This transformation is associated with sizeable costs. Following PEC targets is

more expensive than following strict CO2 reduction targets (see section 6.1.3).

6.1.1 Primary energy consumption and final energy implications

In the baseline scenario, without any limits on PEC consumption and an assumed oil

price of 75 US$2000/bbl, the consumption amounts to 5.2 kW/Cap in the year 2050. In

comparison to today’s consumption of around 5.0 kW/Cap, we see a small

consumption increase. Considering the strong demand increases in most energy

sectors, this small increase in fact reflects large technological energy-efficiency

improvements. However, these energy-efficiency improvements do not come close to

what would be necessary under the umbrella of a 2000-Watt society. Without any

political measures or incentives, the target of a 2000-Watt society is far away from

reality.

Before looking directly at the 2000-Watt society, a sensitivity analysis on oil prices is

conducted. We investigate results for one case with a lower oil price of 50

US$2000/bbl and two cases with higher oil prices of 100 and 125 US$2000/bbl in 2050.

At a lower oil price, the PEC consumption increases to 5.3 and at higher oil prices the

PEC consumption decreases to 5.0 and 4.9 kW/Cap, respectively. The higher the oil

price the more economical it is to invest in better energy-efficient technologies, the

PEC (or kW/Cap) consumption decreases. However, even for expensive oil prices

the PEC consumption remains at high levels.

In order to find the maximum possible PEC reduction a detailed analysis is

conducted. For all levels of oil prices, specific PEC reduction targets are

implemented. Starting at 5.0 kW/Cap, the target is lowered stepwise by 0.5 kW/Cap

until the possible maximum reduction is reached. For all scenarios, independent of

the oil price, a PEC consumption of 3.5 kW/Cap could be achieved – the maximum

reduction is confirmed.


Note that all PEC targets, such as the 3.5 kW/Cap target, are implemented only for

the year 2050 without any intermediate targets. The model is then free to choose the

investment level required to reach the goal without any premature phasing-out of

existing capacities. This approach avoids excess cost penalties at earlier time

periods. By looking at the PEC evolution over time, we can distinguish two

development phases. The first phase starts in the year 2010 and lasts until 2040. The

second phase mirrors the time period of 2040 until 2050. In the first phase, initial

technological changes must be triggered. Compared to the first phase, the second

phase is the more important one. In the second phase, profound changes must be

undertaken in order to realize substantial reduction targets.

With respect to issues of global climate change, we investigate reasonable CO2

emissions targets and combine them with the contemplated PEC objectives. The

sensitivity analysis defines CO2 reductions of 5 % and 10 % per decade, starting from

the Swiss-Kyoto commitment in 2010. Compared to today’s energy-related CO2

emissions, this implies a reduction of 30 and 45 % respectively. By tightening only

CO2 targets, the PEC consumption reduces to values between 4.9 and 4.5 kW/Cap,

depending on the oil price in the year 2050. Compared to present consumption, this

implies a reduction of only 10 % at maximum. Hence, a CO2 reduction alone does not

sufficiently move into the direction of a 2000-Watt society. However, a combination of

CO2 and PEC consumption targets is possible. Independent of the contemplated CO2

reduction, a 3.5 kW/Cap target can be reached and still reflects the lower

consumption limit in the year 2050. Considering that strong CO2 targets can be

reached without significantly lowering the consumption of energy, the goal of the

2000-Watt society remains a questionable instrument to achieve climate-change

mitigation goals.

Implications for the final energy consumption

The energy-reduction constraints on PEC consumption influence the whole energy

system of Switzerland. On the one hand, this is reflected by a reduction of the PEC.

On the other hand, it is reflected by the final-energy (FE) consumption. In the

baseline scenario, the FE consumption in the year 2050 amounts to 871 PJ. Again

this consumption is highly dependent on the oil price if no additional CO2 or kW/Cap

goals are targeted. For the lower oil price of 50 US$2000/bbl the consumption


increases by 6 %, whereas for higher oil prices of 100 and 125 US$2000/bbl the

consumption reduces by 6 and 8 % respectively.

For combined CO2 and PEC scenarios with strong targets, we also observe a

decrease of FE consumption. Investments in energy-efficiency options in the FE

sector take place to a large extend. Thereby, the highest investments in efficient

technologies are made when these combined CO2 and PEC targets are applied. For

significant CO2 reduction targets only, the FE consumption reduces by 16 % to about

735 PJ. For significant combined kW/Cap and CO2 targets, the FE consumption

reduces by more than 26 % to less than 650 PJ in 2050.

The energy use of Switzerland is divided into five end-use sectors, each having

several sub-sectors: Residential, transportation, industry, commercial and agriculture.

All sectors have a different share of FE energy consumption and all sectors show

different reduction levels. The most important sectors are the residential and the

transportation sectors. These sectors are scrutinized in more detail within the scope

of this analysis. The residential sector shows the highest energy reductions

compared to all other sector. The total FE consumption of this sector is reduced to

about 100 PJ in 2050. At an oil price of 75 US$2000/bbl, this implies a reduction of

45 %. Major energy reductions are achieved in the residential heating (RH) sub-

sector. Although this sub-sector remains to be the main consumer of energy, RH

consumes only 43 PJ in 2050. The obtained reductions in the transportation sector

are lower compared to the residential sector. Still, we observe significant reductions.

Passenger cars remain to be the largest consumers in the transportation sector.

While passenger cars use more than 160 PJ of FE in 2000, the consumption could

reduce to around 110 PJ in 2050.

6.1.2 Technological change and CO2 emissions

The analysis showed that during the first half of the century only intermediate steps

towards the 2000-Watt society can be achieved. Even these intermediate steps are

associated with a considerable transformation of the Swiss energy system in terms of

both final-energy production and energy-demand technologies.


Final energy production: Electricity

At the moment, the Swiss production of electricity is dominated by hydro und nuclear

power and is nearly CO2 free. In future, electricity will play an even more important

role in a service-oriented society than today. Electricity can efficiently substitute other

energy carriers, especially fossil energy carriers. Because of this, a CO2 free

electricity production will be of major concern for an overall effective reduction of CO2

emissions in the future. A prime-example for an efficient substitution of fossil energy

carriers with electricity is heat pumps. Electricity can also substitute for oil products

and natural gas in many industrial processes. The question to be answered is:

Should Switzerland invest in nuclear-energy technologies, highly-efficient gas-fired

combined-heat-and-power (CHP) plants or renewable energies? Depending on the

examined target, we observe different results.

Strong CO2 reductions increase the electricity production and therefore the share of

electricity in end-use sectors rises. A CO2 reduction equivalent to 10 % per decade

results in an electricity-production increase of more than 30 % in 2050 compared to

the year 2000. Excluding the exported amount of electricity, we observe an increase

of more than 45 % by 2050. For a 3500-Watt society in 2050, a large amount of

energy-efficiency investments must be undertaken. Therefore, the increase in

electricity production is not as strong as in the CO2 reduction scenarios. In any case,

the electricity production will increase from a today’s level of 57 TWh to 70 - 85 TWh

in 2050, even with a PEC consumption reduction to 3.5 kW/Cap.

Without any CO2 and PEC constraints, nuclear power is the most competitive option

for the production of electricity. We attain the same results by implementing CO2

reduction targets. However, the option of nuclear power disappears for strong PEC

constraints. CHP plants are favoured taking into account an increase of CO2

emissions. The reason is the comparably low efficiency of nuclear power stations. Of

importance are also assumptions on primary-to-final energy-conversion equivalents

of renewable energy technologies. Assuming an conversion equivalent of 100 %,

such as in the newest SFOE statistics, the results favor renewable technologies

compared to fossil-fuel technologies for PEC and combined PEC and CO2 reduction

targets. Nevertheless, the electricity-production structure is crucial for the CO2

emission balance of Switzerland. All affordable and efficient measures against


climate change require the use of new renewable energies as well as nuclear power.

At the same time the hydro-power potential must be used to its full extent.

Energy demand technologies: Residential heating and passenger cars

We investigated transformation changes in two end-use sectors, namely the

residential and transportation sector. Especially dwelling houses and the vehicle fleet

have to undergo significant transformations until 2050 if we want to reduce energy

consumption and lower CO2 emissions at the same time. Less heat consumption and

more heat pumps as well as novel engine drives for cars would be the choice in the

future.

Today, more than 80 % of residential heat in private houses is generated by burning

diesel and natural gas. We can largely avoid these heating systems even if the

expected sum of the Heated Floor Areas (Energy Reference Floor Area - ERFA)

increases by 40 % until 2050. Building energy-efficient houses and renovating

houses based on the Swiss MINERGIE standards could reduce the energy demand

to less than 40 % compared to today’s consumption. At the same time, by using heat

pumps and district heat from centralised biomass and natural gas CHP plant,

Switzerland would depend on fossil energy sources for room heating only to a very

small degree. This would also lower the CO2 emission in the residential sector by

about 10 million tones, which is about 20 % of today’s Swiss CO2 emissions.

Buying more and more cars and driving more kilometres every year but at the same

time wanting to reduce CO2 emissions, the structure of today’s car fleet needs to

change substantially. The car fleet would need to have drastically lower CO2

emissions per driven vehicle-kilometre compared to today’s fleet. Hybrid engines

could replace currently dominating gasoline and diesel internal-combustion engines.

They mark the most cost-effective replacement option, lowering CO2 at the same

time. Gasoline cars, with relative high fuel consumption, would have no future in a

3500-Watt society. Besides diesel cars, natural gas cars would penetrate the market

as natural gas could be used in an efficient manner, also having lower CO2

emissions. However, for a market penetration of natural gas cars, the development of

an infrastructure supporting natural gas fuelling stations is indispensable.

For strong PEC and CO2 reduction target, we also observe a first penetration of

hydrogen cars (with hybrid and fuel-cell engines) in 2045. Even if the volume of traffic


increases by 40 % until 2050, we could achieve a FE reduction of one third and

reduce CO2 emissions by 5 million tones by following the technological pathway

described before. However, the penetration of hydrogen fuel-cell cars largely

depends on the price of fuel-cells and the stack size installed in passenger cars. The

initial date for market penetration could already be around 2030 when the cost of

fuel-cells is lower and light vehicles with an engine size of 50 kW are offered. In

2050, a market share of up to 21 % is possible.

6.1.3 Additional total system costs

The transformation of the energy system is not cost-free. Whereas less stringent

PEC targets are still relatively cheap, strong targets are more expensive. At an oil

price of 75 US$2000/bbl in 2050, the additional costs to reach a 3500-Watt society

amount to about 20 billion US$2000 (~33 billion CHF2000)61. The costs are additional to

the baseline costs at the same oil price and represent cumulative discounted costs.

These costs should be compared to a Kyoto-for-ever target (i.e. 5 % CO2 reduction

per decade), which has about the same CO2 emissions in 2050. The costs to reach a

Kyoto-for-ever are about 15 billion US$2000 (~25 billion CHF2000) or 5 billion US$2000

(~8 billion CHF2000) less, see Figure 67.

0

5

10

15

20

25

30

35

40

45

50

5.2 kW (NoLimit)

4.9 kW (NoLimit)

4.8 kW (NoLimit)

3.5 kW target 3.5 kW target 3.5 kW target


decade


decade


decade


decade

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illi

on

US

$2

00

0]

Figure 66: Total-system-costs increase for an Oil Price of 75US$2000/bbl.

61 In the year 2000, the average exchange rate was 1.68846 CHF to 1 US$.[112]


As mentioned above, strong CO2 targets must be formulated explicitly. If a 10 % CO2

reduction per decade is envisaged additional to the 3.5 kW/Cap target, the extra

costs amount to about 40 billion US$2000 (~67 billion CHF2000). The costs also highly

depend on the oil price in the year 2050. Whereas for lower oil prices the additional

costs increase to more than 45 billion US$2000 (~75 billion CHF2000), for higher oil

prices they reduce to about 35 billion US$2000 (~59 billion CHF2000). However, despite

of possible cost and technology synergies of combined PEC and CO2 targets, to

comply with strong CO2 target is less expensive. A 10 % per decade CO2 reduction

costs between 15 and 30 billion US$2000 (~25 and 50 billion CHF2000), depending on

the oil price in 2050. Therefore, if the main argument in favour of the 3500-Watt

society was CO2 reduction, then the PEC target is questionable.

6.1.4 The influence of discount rates

For long-term policy making the choice of discount rates determines the present

value of these policy-induced costs and benefits. Given controversial issues about

discount rates, we study a low discount rate of 3 % (also used in the baseline

scenario) and a high discount rate of 5 %. These different discount rates are applied

to two scenario sets. The first scenario set represents non-constrained scenarios

where neither PEC consumption nor CO2 are limited. The second scenario set

represents PEC constraint scenarios where a PEC consumption target of 3.5

kW/Cap is applied.

The non-constrained scenarios show a relatively small but notable difference in the

PE consumption. By decreasing the discount rate from 5 % to 3 % the PE

consumption reduces by little more than 3 %. At the same time the amount of oil and

gas consumed in 2050 is less due to investments in more capital-intensive and

energy-efficient technologies. In turn, the total CO2 emissions reduce by 7 % (from

40.3 to 37.7 Mt). On the contrary, the 3.5 kW/Cap constraint scenarios show in

essence no difference in total PE consumption. This effect is reflected in the CO2

emissions in 2050. The emissions differ by less than 0.3%. We can conclude that the

discount-rate changes have only little effect on the PE consumption and on future-

investment choices in Switzerland. Especially, a strong kW/Cap constraint already

demands such capital-intensive technologies that a low discount does not show an

additional effect in favour of these technologies.


6.1.5 Partial equilibrium with elastic demands

The partial equilibrium version of MARKAL assumes elastic end-use demands to

their own prices. The core issue of this analysis is whether or how much more can

the PEC consumption be reduced in comparison to the non-elastic demand

evaluation?

Evaluating the 3.5 kW/Cap PEC-consumption target using an elastic-demand

approach, we attain different PEC consumption shares compared to the evaluation

without elastic demands. The amount of fossil-fuel consumption reduces and nuclear

energy gains share. For high oil prices, all energy demands, such as residential

heating (RH) and driven kilometres of passenger cars, reduce. These reductions lead

to a lower consumption of fossil fuels and are reflected in the PEC balance. As a

result, the production of energy with lower-efficient technologies is possible. Note that

the total PEC consumption is still limited to 3.5 kW/Cap. Therefore, instead of

producing electricity by high-efficient gas power stations, electricity is produced by

less efficient but also less costly nuclear power stations.

Although the demand for energy reduces due to high energy prices, there is still a

limit to the possible demand reduction. At maximum, we can reduce the PEC

consumption to 3.0 kW/Cap in 2050. The 3.0 kW/Cap target can be obtained by

reducing additional demand for electricity, which in turn lowers the PEC consumption

However, note that even by achieving a 3.0 kW/Cap using elastic demands, new

investment in nuclear power station or the extension of their decommissioning time is

favoured.

6.2 Lessons learned

Even by following strict energy-efficiency strategies with the only objective to reduce

the primary-energy per capita (PEC) consumption, a 2000-Watt society can only be

achieved after the year 2050. At the moment one flight from Zürich to Los Angeles

per person and year covers half the limit of a 2000-Watt society. Using the

technologies at hand by the middle of the century, we could lower the primary-energy

consumption to 3500 Watts per capita (or to 3000 Watts taking into account

consumer’s behaviour to price changes) at maximum. The transition of the current

energy system to a 2000-Watt society is highly ambitious. All targeted changes will

not take place on their own. We would need goal-oriented measures from politics

such that people change behaviour and invest in more efficient and cleaner


technologies. Already existing energy-efficiency labelling such as MINERGIE,

energho or Eco-Driver® should be just a beginning. Additional labelling or even

banning of inefficient technologies or subsidizing “intelligent technologies” (e.g.

electronic control engineering in houses and for road and rail transportation) would

be advantageous. At the same these measures would induce innovation from which

the Swiss industry could profit.

To consume less energy is surely important but does it make sense to put everything

on one card: reduction of PEC consumption? By only reducing the PEC

consumption, Switzerland does not reach the destination of a climate-friendly energy

consumption and a sustainable reduction of CO2 emissions in 2050. The import

dependency on fossil-energy carriers and resulting CO2 emissions remain critical.

Renewable energies do not encounter a breakthrough. Therefore, it would be

necessary to combine total PEC consumption targets with upper limits on CO2

emissions. However, despite possible technological synergies, combined PEC and

CO2 targets are available only at very high costs.

Reducing CO2 emissions should actually be the overriding goal, although the energy

consumption is higher. Due to climate political issues, CO2 emissions should reduce

by 50 % until 2050 at least. Therefore, the emissions must reduce by 10 % if not 15

% per decade, assuming that Switzerland reaches the Kyoto target in 2010. This

overriding goal would also make the Swiss air cleaner, without penalizing renewable

energies by a cap on the total energy consumption. Assuming that local pollutants

are proportional to the consumption of fossil fuel, a CO2 reduction by half also has

significant co-benefit on local air quality without direct end-of pipe solutions. The

earlier necessary changes are initiated the easier it will be to reach long-distance

targets.

6.3 Outlook on future research

The results presented here have illustrated some guidelines on how to achieve

intermediate steps towards the 2000-Watt society. For the analysis the cost-

optimisation model Swiss MARKAL (SMM) is used and ready to answer further

research questions. However, due to modelling and time limitations many aspects

were generalized and based on assumption. Two areas of further research emerge

from this study. The first area addresses issues relating to enhancing the modelling


framework. The second area addresses issues relating to extending the scope and

profoundness of the selected policy-portfolio analysis.

SMM could be coupled to a macro-economic model.[105] This way, the bottom-up

representation of the energy system in SMM could better take into account

parameters such as national income, unemployment, inflation, investment or

international trade. Additionally, in view of the currently observed fluctuating energy

prices, uncertainties of energy prices could be incorporated.[113] The impact of

uncertain energy prices on the supply structures and the interaction with measures in

the demand sectors could be of prime interest. The feedbacks from the behaviour of

complex systems could be analysed using system dynamics models. For instance,

the transportation sector is governed not only by most cost-effective options.

Customer behaviour remains critical. Especially access to the fuelling network and

available vehicle options are very important issues.[111] System dynamics models

can help to analyze these important issues.

Additional policy analysis could also offer numerous possibilities to verify and extend

results and conclusions. Despite the variety of sensitivity analyses conducted here,

an extended systematic sensitivity analysis might provide additional insights. The

parameters which could be used for an additional sensitivity are: technology specific

discount rates of future investments, price elasticises of demand sectors, efficiencies

and costs of relevant future technologies and costs and potentials of energy carriers.

Other areas of interest could be internalizing external costs or accounting for grey

energy and other greenhouse gases (GHG).

References 124

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List of figures 133

List of figures

Figure 1: A possible development towards the 2000-Watt society [7] .................................................... 7 Figure 2: A simplified version of the Reference Energy System (RES) used in the energy-system

Swiss-MARKAL model. T&D is an abbreviation for transmission and distribution. ....................... 13 Figure 3: Primary-energy consumption in the baseline scenario for the period 2000 to 2050.............. 19 Figure 4: Primary-energy per capita consumption for the period 1910 to 2050. The figure shows

historic values for the time period 1910 until 2000 and values of the baseline projection for the time period 2000 until 2050. [17,55,56] ......................................................................................... 20

Figure 5: Final-energy consumption by fuels in the baseline scenario for the period 2000 to 2050..... 21 Figure 6: Final-energy consumption by sectors in the baseline scenario for the period 2000 to 2050. 22 Figure 7: Electricity production in the baseline scenario for the time period 2000 to 2050................... 23 Figure 8: Correlation between electricity consumption and GDP for the time period 1980 to 2050. The

time period 1980 to 2000 reflects statistical values and the time period 2000 to 2050 SMM values of the baseline scenario. ................................................................................................................ 24

Figure 9: Energy-related CO2 emissions per sector in Switzerland for the period 2000 to 2050 in the baseline scenario. .......................................................................................................................... 25

Figure 10: ERFA comparison ................................................................................................................ 29 Figure 11: Demolition rate and ERFA existing buildings. ..................................................................... 30 Figure 12: Energy demand existing buildings SFH (RH1) and MFH (RH3).......................................... 30 Figure 13: ERFA new buildings SFH (RH2) and MFH (RH4). .............................................................. 31 Figure 14: Average specific room-heating demand of new buildings built in a future period of time.... 32 Figure 15: Room-heating demand new buildings energy saving options ............................................. 33 Figure 16: Marginal-cost curves for SFH (left) and MFH (right) existing buildings ............................... 35 Figure 17: Marginal-cost curves implementation for SFH existing buildings used for the model

implementation............................................................................................................................... 38 Figure 18: Marginal-cost curve of new buildings SFH – sketch ............................................................ 40 Figure 19: Final-energy consumption of residential demand segments ............................................... 46 Figure 20: Detailed final-energy consumption of the residential heating sector [PJ]. Also depicted in

the figure is the saved energy (grey area) due to improved insulation of roofs, windows, etc and the increase of the (useful-) energy demand. The energy demand (solid line) is illustrated in [per Unit], relative to the year 2000....................................................................................................... 47

Figure 21: Final-energy consumption of the residential sector [PJ] by fuel for all demand categories. 48 Figure 22: Demand increase of passenger cars in [%] ......................................................................... 54 Figure 23: Demand increase of other transportation modes in [%]....................................................... 55 Figure 24: Final-energy consumption of transportation demand segments.......................................... 58 Figure 25: Total final-energy consumption of the transportation sector ................................................ 58 Figure 26: Primary energy per capita [kW/Cap] development for various kW/Cap targets in the year

2050 at an oil price of 75 US$2000/bbl in the year 2050............................................................... 60 Figure 27: Total primary-energy consumption for an oil price of 75 US$2000/bbl in the year 2050........ 61 Figure 28: CO2 Emissions of different scenarios in the year 2050........................................................ 62 Figure 29: Total Final-energy consumption [PJ] developments for various kW/Cap targets and an oil

price of 75 US$2000 in 2050 ............................................................................................................ 63 Figure 30: Total final-energy consumption of the residential sector in 2050......................................... 65 Figure 31: Total final-energy consumption of the residential heating sector......................................... 66 Figure 32: Final-energy savings of the residential sector in 2050......................................................... 67 Figure 33: Specific-heating demand of an average residential house for an oil price of 75 US$2000/bbl

and without a primary energy constraint........................................................................................ 68 Figure 34: Specific-heating demand of an average residential house for an oil price of 75 US$2000/bbl

and a primary energy constraint of 3.5 kW/Cap ............................................................................ 69 Figure 35: Detailed final-energy consumption of the residential heating sector [PJ] for an oil price of 75

US$2000/bbl and a primary energy target of 3.5 kW/Cap in 2050................................................... 70 Figure 36: Comparison of energy demand, final energy consumption and ERFA for an oil price of 75

US$2000/bbl and a primary energy target of 3.5 kW/Cap in 2050................................................... 71 Figure 37: Final-energy consumption of the transport sector in 2050................................................... 72 Figure 38: Final-energy consumption of passenger cars in 2050 ......................................................... 73 Figure 39: Detailed final-energy consumption of passenger cars [PJ] for an oil price of 75 US$2000/bbl

and a primary energy target of 3.5 kW/Cap in 2050...................................................................... 73 Figure 40: CO2 emission targets ........................................................................................................... 74 Figure 41: Primary energy per capita [kW/Capita] for an oil price of 50 US$2000/bbl in 2050 ............... 76

List of figures 134

Figure 42: Primary energy per capita [kW/Cap] consumption for oil prices of 50 and 100US$/bbl2000, no and 10% per decade CO2 reductions as well as no and 3.5kW/Cap primary energy constraints. 78

Figure 43: Primary energy per capita [kW/Cap] consumption for an Oil Price of 125 US$/bbl2000, various CO2 limits and a primary per capita constraint of 3.5kW/Cap........................................... 79

Figure 44: Primary energy per capita [kW/Cap] development for various kW/Cap and CO2 targets in the year 2050 at an oil price of 75 US$2000/bbl in the year 2050 ................................................ 80

Figure 45: Detailed final-energy consumption of the residential heating sector [PJ] for an oil price of 75 US$2000/bbl, a primary energy target of 3.5 kW/Cap in 2050 and a CO2 reduction target of 10 % 82

Figure 46: Comparison of energy demand, final energy consumption and ERFA for an oil price of 75 US$2000/bbl, a primary energy target of 3.5 kW/Cap in 2050 and a CO2 reduction target of 10 % 82

Figure 47: Detailed final-energy consumption of passenger cars [PJ] for an oil price of 75 US$2000/bbl and a primary energy target of 3.5 kW/Cap in 2050 and a CO2 reduction target of 10 %. .......... 83

Figure 48: Electricity production [TWh] for an oil price of 75 US$2000/bbl and various CO2 emission and primary energy targets................................................................................................................... 85

Figure 49: Primary energy consumption [PJ] of renewable energy technologies for various CO2 and kW/Cap limits and an oil price of 75 US$2000/bbl. .......................................................................... 86

Figure 50: Primary energy consumption [PJ] of wood technologies for an oil price of 75 US$2000/bbl. A 3.5 kW/Cap target and 10 % CO2 reduction are applied. .............................................................. 87

Figure 51: Total-system-costs increase for an Oil Price of 75US$2000/bbl ............................................ 88 Figure 52: Annual total-system-costs increase for an oil price of 75US$2000/bbl .................................. 90 Figure 53: Primary energy per capita [kW/Cap] consumption for an oil price of 75 US$2000/bbl with

discount rates (dr) of 3 and 5 % as well as no kW/Cap target and a 3.5 kW/Cap target .............. 93 Figure 54: Final-energy consumption of passenger cars at an oil price of 75US2000/bbl, 3.5 kW/Cap

primary energy and a CO2 reduction constraint of 10 % per decade. Fuel stack price is assumed to be 300US$/kW in 2010 and the size of one fuel cell is 50 kW. ................................................. 95

Figure 55: Partial equilibrium model with elastic demands (based on [98,99])..................................... 98 Figure 56: Primary energy per capita [kW/Cap] consumption for an oil price of 75 US$2000/bbl with and

with elastic demand calculations ................................................................................................. 100 Figure 57: Wood-based process chains for bio-fuel production from wood considered in the SWISS-

MARKAL model. CNG stands for compressed natural gas and ICE stands for internal combustion engine. ......................................................................................................................................... 101

Figure 58: Wood-based process chains for combined heat and power (CHP) production considered in the SWISS-MARKAL model. For simplicity, transmission and distribution processes are not shown in the diagram................................................................................................................... 102

Figure 59: Wood-based process chains for heat production considered in the SWISS-MARKAL model. The abbreviation SFH stands for Single Family Houses. For simplicity, transmission and distribution processes are not shown in the diagram. ................................................................. 102

Figure 60: Primary-energy use of wood by different technologies for oil prices between 100 and 130 US$2000/bbl in the year 2050. The Fischer-Tropsch synthesis is not included as an option........ 104

Figure 61: Final-energy consumption by fuel of the transport sector for oil prices between 100 and 130 US$2000/bbl in the year 2050. ....................................................................................................... 106

Figure 62: Market penetration of the methanation plant for different oil prices and subsidies levels. The market penetration in the figure corresponds to the use of biomass for the Methanation processes expressed in [PJ]. ........................................................................................................................ 108

Figure 63: Market penetration of the methanation plant for different investment cost (high, medium, low). The market penetration in the figure corresponds to the use of biomass for the Methanation processes expressed in [PJ]. ....................................................................................................... 109

Figure 64: Primary-energy use of wood for an oil price of 80 US$2000/bbl in 2050 and bio-SNG subsidies of 4 US$/GJ. ................................................................................................................ 111

Figure 65: Total primary-energy consumption development for various kW/Cap targets and an oil price of 50 US$2000/bbl .......................................................................................................................... 144

Figure 66: Total primary-energy consumption development for various kW/Cap targets and an oil price of 75 US$2000/bbl .......................................................................................................................... 144

Figure 67: Total primary-energy consumption development for various kW/Cap targets and an oil price of 100 US$2000/bbl ........................................................................................................................ 145

Figure 68: Total primary-energy consumption development for various kW/Cap targets and an oil price of 125 US$2000/bbl ........................................................................................................................ 145

Figure 69: Primary-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 50US$2000/bbl ............................................................................................................. 146

Figure 70: Primary-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl ............................................................................................................ 146

List of figures 135

Figure 71: Primary-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl .......................................................................................................... 147

Figure 72: Primary-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl .......................................................................................................... 147

Figure 73: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 50 US$2000/bbl ................................................................................................................. 148

Figure 74: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 75 US$2000/bbl ................................................................................................................. 148

Figure 75: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 100 US$2000/bbl ............................................................................................................... 149

Figure 76: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 125 US$2000/bbl ............................................................................................................... 149

Figure 77: Final-energy consumption per sector in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl ............................................................................................................ 150

Figure 78: Final-energy consumption per sector in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl ............................................................................................................ 150

Figure 79: Final-energy consumption per sector in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl .......................................................................................................... 151

Figure 80: Final-energy consumption per sector in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl .......................................................................................................... 151

Figure 81: Final-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl ................................................................................................................. 152

Figure 82: Final-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl ................................................................................................................. 152

Figure 83: Final-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl ............................................................................................................... 153

Figure 84: Final-energy consumption per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl ............................................................................................................... 153

Figure 85: Final-energy consumption residential sector in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl ................................................................................................ 154

Figure 86: Final-energy consumption residential sector in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl ................................................................................................ 154

Figure 87: Final-energy consumption residential sector in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl .............................................................................................. 155

Figure 88: Final-energy consumption residential sector in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl .............................................................................................. 155

Figure 89: Final-energy consumption residential heating in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl ................................................................................................ 156

Figure 90: Final-energy consumption residential heating in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl ................................................................................................ 156

Figure 91: Final-energy consumption residential heating in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl .............................................................................................. 157

Figure 92: Final-energy consumption residential heating in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl .............................................................................................. 157

Figure 93: Final-energy consumption transportation sector in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl .................................................................................... 158

Figure 94: Final-energy consumption transportation sector in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl .................................................................................... 158

Figure 95: Final-energy consumption transportation sector in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl .................................................................................. 159

Figure 96: Final-energy consumption transportation sector in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl .................................................................................. 159

Figure 97: Final-energy consumption passenger cars in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl ....................................................................................................... 160

Figure 98: Final-energy consumption passenger cars in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl ....................................................................................................... 160

Figure 99: Final-energy consumption passenger cars in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl ..................................................................................................... 161

Figure 100: Final-energy consumption passenger cars in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl .............................................................................................. 161

Figure 101: Electricity production per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 50 US$2000/bbl .......................................................................................................................... 162

List of figures 136

Figure 102: Electricity production per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 75 US$2000/bbl .......................................................................................................................... 162

Figure 103: Electricity production per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 100 US$2000/bbl ........................................................................................................................ 163

Figure 104: Electricity production per fuel in 2050 for various kW/Cap and CO2 targets and an oil price of 125 US$2000/bbl ..................................................................................................................... 163

Figure 105: Total system costs increase for an oil price of 50 US$2000/bbl......................................... 164 Figure 106: Total system costs increase for an oil price of 75 US$2000/bbl......................................... 164 Figure 107: Total system costs increase for an oil price of 100 US$2000/bbl....................................... 165 Figure 108: Total system costs increase for an oil price of 125 US$2000/bbl....................................... 165 Figure 109: Total system costs increase over time for various CO2 targets and an oil price of 50

US$2000/bbl ................................................................................................................................... 166 Figure 110: Total system costs increase over time for various CO2 targets and an oil price of 75



US$2000/bbl ................................................................................................................................... 167 Figure 113: Total system costs increase over time for various CO2 targets, a 3.5 kW/Cap target and an

oil price of 50 US$2000/bbl ............................................................................................................ 168 Figure 114: Total system costs increase over time for various CO2 targets, a 3.5 kW/Cap target and an

oil price of 75 US$2000/bb ............................................................................................................. 168 Figure 115: Total system costs increase over time for various CO2 targets, a 3.5 kW/Cap target and an

oil price of 100 US$2000/bb ........................................................................................................... 169 Figure 116: Total system costs increase over time for various CO2 targets, a 3.5 kW/Cap target and an

oil price of 125 US$2000/bbl .......................................................................................................... 169

List of tables 137

List of tables

Table 1: Prices for fossil energy resources as assumed in this study. For a better understanding, the oil price is given both in US$/GJ and in US$/bbl. .......................................................................... 15

Table 2: Demand segments of the residential sector ............................................................................ 26 Table 3: Final-energy consumption 2000 – split by demand segments and fuels ................................ 26 Table 4: Future heating technologies .................................................................................................... 28 Table 5: Five-year period renovation rates of existing buildings [%]..................................................... 37 Table 6: End-use demand of residential demand segments [PJ].......................................................... 42 Table 7: Adratios residential sector ....................................................................................................... 44 Table 8: Demand segments of the transportation sector ...................................................................... 49 Table 9: Fuel consumption of the transportation sector in [PJ] in 2000 ................................................ 51 Table 10: Stock of vehicles [1000 Vehicels].......................................................................................... 52 Table 11: Changes of stock of vehicles due to tank tourism [1000 Vehicles] ....................................... 52 Table 12: Kilometres per vehicle travelled per annum [Vkm/ Vehicle / a] ............................................. 52 Table 13: Average efficiency of vehicles 2000 [Lt/100km] .................................................................... 52 Table 14: Conversion factors PJ to Lt for different fuels ....................................................................... 52 Table 15: Total Final-energy consumption vehicles.............................................................................. 53 Table 16: Demand segments of other transportation modes ................................................................ 55 Table 17: Adratios transportation sector ............................................................................................... 56

Appendix 138

Appendix 1: Technological description of room-heating technologies

Oil Natural Gas Heat Pump Pellets Biomass Pellets / Oil / Natural Gas / District Heat

Sole Air Water Solar Solar Solar

Room-Heating Single-Family Houses Existing Building (RH1)

INVCOST [mUS$2000/PJ/a] 297.0 288.6 412.6 334.9 438.4 379.9 424.5 475.5 410.0 364.1 -

FIXOM [mUS$2000/PJ/a] 7.4 9.8 12.7 10.3 11.5 13.7 13.7 14.7 9.4 10.8 -

η [%] 0.98 0.99 3.40 2.60 4.00 0.82 0.82 0.82 0.98 0.99 -

Room-Heating Single-Family Houses New Building (RH2)

INVCOST [mUS$2000/PJ/a] 298.9 295.4 422.6 342.7 441.2 389.0 427.2 487.0 419.9 372.9 -

FIXOM [mUS$2000/PJ/a] 7.8 9.1 9.7 10.0 9.9 15.3 13.7 16.3 9.8 10.1 -

η [%] 0.98 0.99 3.40 2.60 4.00 0.82 0.82 0.82 0.98 0.99 -

Room-Heating Multi-Family Houses Existing Buildings (RH3)

INVCOST [mUS$2000/PJ/a] 101.8 100.2 214.3 138.1 185.0 130.4 158.0 164.6 148.0 131.5 228.2

FIXOM [mUS$2000/PJ/a] 2.1 4.5 6.4 4.8 5.6 9.8 9.8 10.8 3.1 5.5 4.1

η [%] 0.98 0.99 3.60 2.80 4.00 0.85 0.85 0.85 0.98 0.99 0.86

Room-Heating Multi-Family Houses New Buildings (RH4)

INVCOST [mUS$2000/PJ/a] 103.4 101.6 217.3 140.0 187.8 132.2 160.4 166.9 150.1 133.3 231.7

FIXOM [mUS$2000/PJ/a] 2.6 4.5 6.4 5.0 5.6 10.9 10.9 11.9 3.6 5.5 4.1

η [%] 0.98 0.99 3.60 2.80 4.00 0.85 0.85 0.85 0.98 0.99 0.86

References: [114], [115], [116], [117], [69], own assumptions

INVCOST: Investment Costs; FIXOM: Fixed Costs; η: �Efficiency

Appendix 139

Appendix 2: Technological description of passenger cars

Investment costs O&M Costs Efficiency Fuel Engine

[mil. US$2000/bil. v-km] [mil. US$2000/bil. v-km] [bil. v-km/PJ]

Gasoline Internal Combustion Engine 1292.2 25.8 0.53

Electric Hybrid 1410.3 28.2 0.61

Hybrid Fuel Cell 5297.3 105.9 0.62

Diesel Internal Combustion Engine 1053.2 21.1 0.56


Compressed Natural Gas

Internal Combustion Engine 1340.8 26.8 0.52


Hydrogen Internal Combustion Engine 1551.5 31.0 0.60


Fuel Cell 4341.1 86.8 1.06

Hybrid Fuel Cell 4414.2 88.3 1.19

References: [97,98]

bil.: billon

mil.: million

v-km: vehicle kilometers

Appendix 140

Appendix 3: Biomass technology description

Technology Electric Efficiency [%]

Thermal Efficiency [%]

Capacity [MW]

Investment Costs

[CHF/kW]

Fixed O&M Costs [CHF/kW]

Variable O&M Costs [Rp/kWh]

Plant Factor [hours/year]

Methanation 55 (bio-SNG) 10 100 1583 55.4 0.198 8000

Fischer-Tropsch (FT) Synthesis 10 45 (FT

Diesel) 400 1553 54.3 0.194 8000

Decentralized CHP 40 40 0.5 1500 52.5 0.375 4000

Wood CHP (<2MWe) Gasification 25 50 8 2000 70 0.5 4000

Wood CHP (<2MWe) Combustion 12 65.3 0.45 7815 273.5 1.95 4000

Wood CHP (>2MWe) Gasification 43.3 42.9 138.5 2200 77 0.55 4000

Wood CHP (>2MWe) Combustion 12.4 63.2 26.6 596 20.9 0.149 4000

Gas heating in SFH - 100 10 1500 52.5 0.75 2000

Wood chips heating (50 kWth) - 80 0.05 1700 59.5 0.85 2000



Pellet heating in SFH - 95 0.01 2500 87.5 1.25 2000

Wood chips + Nat. Gas Combustion 45 - 75 2000 70 0.25 8000

References : [51,118-121]

Appendix 141

Appendix 4: Final-energy calibration of the Swiss MARKAL model (SMM) to SFOE and IEA

statistic of the year 2000

SFOE [1] Oil Products Electricity Gas Coal Wood / Charcoal District heat Waste Other renewable energies Total

Residential 121.0 56.6 36.3 0.1 8.6 4.6 0.0 3.4 230.6 Industry 41.5 65.1 31.9 5.6 7.0 5.6 11.4 0.4 168.5 Commerce 51.7 53.8 21.2 0.0 3.5 3.0 4.4 2.1 139.6 Transport 293.3 9.5 0.0 0.0 0.0 0.0 0.0 0.0 302.8 Non-Energy Use 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Other non-specified 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Agriculture 3.0 3.6 5.8 0.1 0.9 0.1 0.0 0.4 13.9

Total 510.4 188.5 95.2 5.9 20.0 13.3 15.7 6.3 855.3

IEA [49] Oil Products Electricity Gas Coal Wood / Charcoal District heat Waste Other renewable energies Total

Residential 124.3 56.6 36.3 0.5 8.9 4.6 0.0 3.5 234.6 Industry 42.5 65.1 37.5 10.1 6.8 5.6 11.3 0.3 179.3 Commerce 56.3 53.8 21.2 0.0 3.4 3.0 0.0 0.6 138.3 Transport 286.0 9.5 0.0 0.0 0.0 0.0 0.0 0.0 295.5 Non-Energy Use 18.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 18.1 Other non-specified 4.5 0.0 4.1 0.0 0.0 0.1 0.0 0.0 8.8 Agriculture 6.1 3.6 0.0 0.0 0.9 0.0 0.0 0.4 11.0

Total 537.8 188.6 99.1 10.6 20.0 13.3 11.3 4.8 885.5

SMM Calibration Oil Products Electricity Gas Coal Wood / Charcoal District heat Waste Other renewable energies Total Residential 121.5 55.1 37.9 0.4 8.5 5.1 0.0 3.5 232.1 Industry 44.8 63.9 36.9 5.7 7.4 5.3 12.3 0.0 176.3 Commerce 52.5 55.2 20.4 0.0 3.3 3.1 0.0 0.5 135.0 Transport 293.3 9.5 0.0 0.0 0.0 0.0 0.0 0.0 302.8 Non-Energy Use 16.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 16.4 Other non-specified 4.7 5.3 0.0 0.0 0.0 0.0 0.0 10.1 Agriculture 5.7 3.4 0.0 0.0 0.9 0.0 0.0 0.4 10.5 Total 538.9 187.2 100.6 6.2 20.1 13.5 12.3 4.4 883.2

Unit: [PJ]

Appendix 142

Appendix 5: Oil-price sensitivity

The results present here comprise various model results, including primary-energy

consumption, final-energy consumption, electricity consumption and total-system

costs. Each result is illustrated for oil prices of 50, 75, 100 and 125 US$2000/bbl in the

year 2050. In detail, the following results presented comprise:

Appendix 5.1: Primary Energy Balances

• Total primary-energy consumption development for various kW/Cap targets

• Primary-energy consumption per energy carrier in 2050 for various kW/Cap

and CO2 targets

Appendix 5.2: Final Energy Balances

• Total final-energy consumption developments for various kW/Cap targets

• Final-energy consumption per sectors in 2050 for various kW/Cap and CO2

targets

• Final-energy consumption per energy carriers in 2050 for various kW/Cap and

CO2 targets

• Final-energy consumption residential sector in 2050 for various kW/Cap and

CO2 targets

• Final-energy consumption residential heating in 2050 for various kW/Cap and

CO2 targets

• Final-energy consumption transportation sector in 2050 for various kW/Cap

and CO2

• Final-energy consumption passenger cars in 2050 for various kW/Cap and

CO2 targets

Appendix 5.3 Electricity Balance

• Electricity production in 2050 for various kW/Cap and CO2 targets

Appendix 5.4: Total System Costs

• Total system costs increase for an oil price of 100US$2000/bbl

• Total system costs increase over time for various CO2 targets

Appendix 143

• Total system costs increase over time for various CO2 targets and a 3.5

kW/Cap target

Appendix 144

Appendix 5.1: Primary-energy balances

0

1

2

3

4

5

6

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pri

mary

En

erg

y p

er

Cap

ita [

kW

/Cap

]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 67: Total primary-energy consumption development for various kW/Cap targets and an oil price of 50

US$2000/bbl.

0

1

2

3

4

5

6

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pri

mary

En

erg

y p

er

Cap

ita [

kW

/Cap

]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target


US$2000/bbl.

Appendix 145

0

1

2

3

4

5

6

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pri

mary

En

erg

y p

er

Cap

ita [

kW

/Cap

]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target


US$2000/bbl.

0

1

2

3

4

5

6

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pri

mary

En

erg

y p

er

Cap

ita [

kW

/Cap

]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target


US$2000/bbl.

Appendix 146

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

5.3

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Pri

mary

En

erg

y [

kW

/Cap

ita

]


Energycarriers:

PEC target

CO2 limit

Figure 71: Primary-energy consumption per energy carriers in 2050 for various kW/Cap and CO2 targets and

an oil price of 50US$2000/bbl.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

5.2

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Pri

mary

En

erg

y [

kW

/Cap

ita

]


Energycarriers:

PEC target

CO2 limit


an oil price of 75 US$2000/bbl.

Appendix 147

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

5.0

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.7

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Pri

mary

En

erg

y [

kW

/Cap

ita]


Energycarriers:

PEC target

CO2 limit



0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

4.6

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Pri

mary

En

erg

y [

kW

/Cap

ita]


Energycarriers:

PEC target

CO2 limit



Appendix 148

Appendix 5.2: Final-energy balances

0

100

200

300

400

500

600

700

800

900

1000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

To

tal F

inal-

En

erg

y C

on

su

mp

tio

n [

PJ]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 75: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 50

US$2000/bbl.

0

100

200

300

400

500

600

700

800

900

1000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 76: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of 75

US$2000/bbl.

Appendix 149

0

100

200

300

400

500

600

700

800

900

1000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 77: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of

100 US$2000/bbl.

0

100

200

300

400

500

600

700

800

900

1000

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ]

No kW/Cap target

5.0 kW/Cap target

4.5 kW/Cap target

4.0 kW/Cap target

3.5 kW/Cap target

Figure 78: Total final-energy consumption [PJ] developments for various kW/Cap targets and an oil price of

125 US$2000/bbl.

Appendix 150

0

100

200

300

400

500

600

700

800

900

1000

5.3

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]

IndustrialTransportResidentialCommercialAgricultureOther non-specifiedNon-Energy Use

Sectors:

PEC target

CO2 limit

Figure 79: Final-energy consumption per sectors in 2050 for various kW/Cap and CO2 targets and an oil price

of 50 US$2000/bbl.

0

100

200

300

400

500

600

700

800

900

1000

5.2

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]


Sectors:

PEC target

CO2 limit


of 75 US$2000/bbl.

Appendix 151

0

100

200

300

400

500

600

700

800

900

1000

5.0

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.7

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]


Sectors:

PEC target

CO2 limit


of 100 US$2000/bbl.

0

100

200

300

400

500

600

700

800

900

1000

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

4.6

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]


Sectors:

PEC target

CO2 limit


of 125 US$2000/bbl.

Appendix 152

0

100

200

300

400

500

600

700

800

900

1000

5.3

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]

RenewablesWoodCoalGasElectricityOilWasteHeat

Energycarriers:

PEC target

CO2 limit

Figure 83: Final-energy consumption per energy carriers in 2050 for various kW/Cap and CO2 targets and an

oil price of 50 US$2000/bbl.

0

100

200

300

400

500

600

700

800

900

1000

5.2

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]


Energycarriers:

PEC target

CO2 limit



Appendix 153

0

100

200

300

400

500

600

700

800

900

1000

5.0

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.7

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]


Energycarriers:

PEC target

CO2 limit



0

100

200

300

400

500

600

700

800

900

1000

5.2

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al-

En

erg

y C

on

su

mp

tio

n [

PJ

]


Energycarriers:

PEC target

CO2 limit



Appendix 154

0

50

100

150

200

250

300

5.3

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al E

ne

rgy

Co

ns

um

pti

on

[P

J]

Energy SavingsRenewablesHeatWoodGasElectricityOil

Energycarriers & savings:

PEC target

CO2 limit

Figure 87: Final-energy consumption residential sector in 2050 for various kW/Cap and CO2 targets and an oil

price of 50 US$2000/bbl.

0

50

100

150

200

250

300

5.2

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]



PEC target

CO2 limit



Appendix 155

0

50

100

150

200

250

300

5.0

kW

(N

o L

imit)

4.9

kW

(N

o L

imit)

4.7

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al E

ne

rgy

Co

ns

um

pti

on

[P

J]



PEC target

CO2 limit



0

50

100

150

200

250

300

4.9

kW

(N

o L

imit)

4.8

kW

(N

o L

imit)

4.6

kW

(N

o L

imit)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al E

ne

rgy

Co

ns

um

pti

on

[P

J]



PEC target

CO2 limit



Appendix 156

0

25

50

75

100

125

150

175

200

5.3kW(No

Limit)

4.9kW(No

Limit)

4.9kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]

BiomassOtherOilHeatNatural GasElectricity

Energy carriers:

PEC target

CO2 limit

Figure 91: Final-energy consumption residential heating in 2050 for various kW/Cap and CO2 targets and an


0

25

50

75

100

125

150

175

200

5.2kW(No

Limit)

4.9kW(No

Limit)

4.8kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al E

nerg

y C

on

su

mp

tio

n [

PJ

]


Energy carriers:

PEC target

CO2 limit



Appendix 157

0

25

50

75

100

125

150

175

200

5.0kW(No

Limit)

4.9kW(No

Limit)

4.7kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energy carriers:

PEC target

CO2 limit



0

25

50

75

100

125

150

175

200

4.9kW(No

Limit)

4.8kW(No

Limit)

4.6kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energy carriers:

PEC target

CO2 limit



Appendix 158

0

50

100

150

200

250

300

350

5.3kW(No

Limit)

4.9kW(No

Limit)

4.9kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]

HydrogenGasElectricityOil

Energy carriers:

PEC target

CO2 limit

Figure 95: Final-energy consumption transportation sector in 2050 for various kW/Cap and CO2 targets and an


0

50

100

150

200

250

300

350

5.2kW(No

Limit)

4.9kW(No

Limit)

4.8kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energy carriers:

PEC target

CO2 limit



Appendix 159

0

50

100

150

200

250

300

350

5.0kW(No

Limit)

4.9kW(No

Limit)

4.7kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energy carriers:

PEC target

CO2 limit



0

50

100

150

200

250

300

350

4.9kW(No

Limit)

4.8kW(No

Limit)

4.6kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energy carriers:

PEC target

CO2 limit



Appendix 160

0

25

50

75

100

125

150

5.3kW(No

Limit)

4.9kW(No

Limit)

4.9kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]

HydrogenNatural GasGasolineDiesel

Energycarriers:

PEC target

CO2 limit

Figure 99: Final-energy consumption passenger cars in 2050 for various kW/Cap and CO2 targets and an oil


0

25

50

75

100

125

150

5.2kW(No

Limit)

4.9kW(No

Limit)

4.8kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energycarriers:

PEC target

CO2 limit



Appendix 161

0

25

50

75

100

125

150

5.0kW(No

Limit)

4.9kW(No

Limit)

4.7kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energycarriers:

PEC target

CO2 limit



0

25

50

75

100

125

150

4.9kW(No

Limit)

4.8kW(No

Limit)

4.6kW(No

Limit)

5.0kW

5.0kW

5.0kW

4.5kW

4.5kW

4.5kW

4.0kW

4.0kW

4.0kW

3.5kW

3.5kW

3.5kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Fin

al

En

erg

y C

on

su

mp

tio

n [

PJ]


Energycarriers:

PEC target

CO2 limit



Appendix 162

Appendix 5.3: Electricity balance

0

10

20

30

40

50

60

70

80

90

5.3

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ele

ctr

icit

y P

rod

ucti

on

[T

Wh

]

Biomass CogenerationNatural Gas CogenerationSolar PowerWind TurbinesBiomass ThermalConventional Thermal and OthersNuclear PowerHydro Power


PEC target

CO2 limit

Figure 103: Electricity production in 2050 for various kW/Cap and CO2 targets and an oil price of 50

US$2000/bbl.

0

10

20

30

40

50

60

70

80

90

5.2

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

4.8

kW (

No

Lim

it)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ele

ctr

icit

y P

rod

ucti

on

[T

Wh

]



PEC target

CO2 limit


US$2000/bbl.

Appendix 163

0

10

20

30

40

50

60

70

80

90

5.0

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

4.7

kW (

No

Lim

it)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ele

ctr

icit

y P

rod

ucti

on

[T

Wh

]



PEC target

CO2 limit


US$2000/bbl.

0

10

20

30

40

50

60

70

80

90

4.9

kW (

No

Lim

it)

4.8

kW (

No

Lim

it)

4.6

kW (

No

Lim

it)

5.0

kW

5.0

kW

5.0

kW

4.5

kW

4.5

kW

4.5

kW

4.0

kW

4.0

kW

4.0

kW

3.5

kW

3.5

kW

3.5

kW

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ele

ctr

icit

y P

rod

ucti

on

[T

Wh

]



PEC target

CO2 limit


US$2000/bbl.

Appendix 164

Appendix 5.4: Total system costs

0

5

10

15

20

25

30

35

40

45

50

5.3

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

5.0

kW ta

rget

5.0

kW ta

rget

5.0

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$

20

00]

Series1

PEC target

CO2 limit

Figure 107: Total system costs increase for an oil price of 50 US$2000/bbl.

0

5

10

15

20

25

30

35

40

45

50

5.2

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

4.8

kW (

No

Lim

it)

5.0

kW ta

rget

5.0

kW ta

rget

5.0

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$

20

00]

Series1

PEC target

CO2 limit


Appendix 165

0

5

10

15

20

25

30

35

40

45

50

5.0

kW (

No

Lim

it)

4.9

kW (

No

Lim

it)

4.7

kW (

No

Lim

it)

5.0

kW ta

rget

5.0

kW ta

rget

5.0

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$

20

00]

Series1

PEC target

CO2 limit


0

5

10

15

20

25

30

35

40

45

50

4.9

kW (

No

Lim

it)

4.8

kW (

No

Lim

it)

4.6

kW (

No

Lim

it)

5.0

kW ta

rget

5.0

kW ta

rget

5.0

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.5

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

4.0

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

3.5

kW ta

rget

0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10% 0% 5% 10%

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$

20

00]

Series1

PEC target

CO2 limit


Appendix 166

-5

0

5

10

15

20

25

30

35

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]

5 % CO2 limit 10 % CO2 limit

Figure 111: Total system costs increase over time for various CO2 targets and an oil price of 50 US$2000/bbl.

-5

0

5

10

15

20

25

30

35

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]



Appendix 167

-5

0

5

10

15

20

25

30

35

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]



-5

0

5

10

15

20

25

30

35

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]



Appendix 168

-10

0

10

20

30

40

50

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]

no CO2 limit 5 % CO2 limit 10 % CO2 limit

Figure 115: Total system costs increase over time for various CO2 targets, a 3.5 kW/Cap target and an oil price

of 50 US$2000/bbl.

-10

0

10

20

30

40

50

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]



of 75 US$2000/bbl.

Appendix 169

-10

0

10

20

30

40

50

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]



of 100 US$2000/bbl.

-10

0

10

20

30

40

50

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Total

Ad

dit

ion

al T

ota

l-S

yste

m C

osts

[b

illio

n U

S$2000]



of 125 US$2000/bbl.

Curriculum Vitae 170

Curriculum Vitae

Name: Thorsten Frank Schulz

Date of birth: January 13th, 1977

Place of birth: Darmstadt, Germany

Nationality: German

Academic qualifications

PhD studies in Energy Policy Assessment

Swiss Federal Institute of Technology (ETH) Zurich, Switzerland 01/2004 – 06/2007

• Degree: Dr. sc. ETH Zürich

• Topic: Intermediate Steps towards the 2000-Watt Society in Switzerland:

Graduate studies in Environmental Engineering

University of Stuttgart, Germany 10/1997 – 09/2003

• Degree: Dipl.-Ing.

• Topic: Integrated Environmental and Climatic Strategies for the South African Electricity Sector

Abitur

Justus-Liebig-School, Darmstadt, Germany 09/1995 – 06/1997

• German university entrance degree

High School Graduation Diploma

Crocus Plains Regional Secondary School, Brandon, Canada 08/1994 – 07/1995

• Year 12 certificate

Scholarships

Country-Foundation Baden-Württemberg Scholarship 04/2003 – 08/2003

• Research exchange to the Energy Research Centre (ERC), University of Cape Town

German Academic Exchange Service (DAAD) Scholarship 02/2001 – 12/2001

• Academic student exchange to the Energy Research Centre (ERC), University of Cape Town

(UCT), South Africa

(UCT), South Africa

An Energy-Economic Scenario Analysis

Curriculum Vitae 171

Selected Publications and Technical Reports Schulz T.F., Kypreos S. Barreto L., Wokaun A.: Intermediate Steps towards the 2000-Watt Society in Switzerland: An energy-economic scenario analysis. Energy Policy (2007), submitted, July 2007. Bauer C., Schulz T.F., Hirschberg S., Jermann M., Wokaun A.: The 2000-Watt-Society: Standard or guidepost?. Energie-Spiegel, Facts for the Energy Decisions of Tomorrow, Nr. 18, ISSN 1661-5115, Paul Scherrer Institute, Villigen, Switzerland, April 2007. Schulz T.F., Barreto L., Kypreos S. Sticki S.: Assessing wood-based synthetic natural gas technologies using the SWISS-MARKAL model. Energy (2007), doi:10.1016/j.energy.2007.03.006, March 2007. Barreto L., Schulz T.F., Kypreos S.: Impact of CO2 Constraints on the Swiss Energy System: A long-term Analysis with the Swiss-MARKAL Model. Contribution to the NCCR-Climate WP4 Report to the Swiss Federal Office for the Environment (FOEN) on "Climate Vulnerability and Policy in a Post-Kyoto World". Energy Economics Group, Laboratory for Energy Systems Analysis, The Energy Departments, Paul Scherrer Institute, Villigen, Switzerland, January 2007. Schulz T.F., Kypreos S.: Country Report for Switzerland, Description of the Swiss-TIMES model for the New Energy Externatlities Development for Sustainability (NEEDS). Final Country Report for Research Stream 2a: Energy systems modelling and internalisation strategies, including scenario building. Energy Economics Group, Laboratory for Energy Systems Analysis, The Energy Departments, Paul Scherrer Institute, Villigen, Switzerland, December 2006. Wokaun A., Kypreos S., Barreto L., Krzyzanowski D.A., Rafaj P., Schulz T.F.: Strategies for a Cost-Efficient Climate Protection Policy (in German). Boxenstopp – der Tagungsband, 17. May 2005. NFS Klima, Schweizer Klimaforschung, Bern, Switzerland, 2005. Stucki S., Vogel F., Biollaz S., Schulz T.F., Bauer C.: SFOE Energy Perspectives Biomass, Renewable Energy, and new Nuclear Plants: Potentials and Costs, BFE Energieperspektiven Biomasse, Erneuerbare Energien und neue Nuklearanlagen: Potenziale und Kosten (in German). PSI Scientific Report Nr. 05-04, ISSN 1019-0643. Paul Scherrer Institute (PSI) for the Swiss Federal Office of Energy (SFOE), Villigen, Switzerland, May 2005. Schulz T.F., Barreto L., Kypreos S., Wokaun A.: Steps Towards a 2000 Watt Society. PSI Scientific Report 2004, Volume V, ISSN 1423-7342. Energy Economics Group, General Energy Research Department, Paul Scherrer Institute (PSI), Villigen, Switzerland, March 2005. Schulz T.F.: Integrated Environmental and Climatic Strategies for the South African Electricity Sector. Master Thesis, Diplomarbeit. Energy Research Centre (ERC), University of Cape Town (UCT), South Africa and Institute of Energy Economics and Rational Use of Energy (IER), University of Stuttgart, Germany, September 2003.

Selected Conference Proceedings Schulz T.F., Barreto L., Kypreos S., Stucki S.: Assessing Wood-Based Synthetic Natural Gas (Bio-SNG) Technologies. Poster presentation at the NCCR Climate Summer School, Grindelwald, Switzerland, 27 August – 1 September 2006. Schulz T.F, Barreto L., Kypreos S., Stucki S.: Assessing Wood-Based Synthetic Natural Gas Technologies using the Swiss-MARKAL model. International Energy Workshop organized by Research Centre (ERC) University of Cape Town, Energy Modeling Forum (EMF) Stanford University, International Energy Agency (IEA) and the International Institute for Applied System Analysis (IIASA), Cape Town, South Africa, 27-29 June 2006. Schulz T.F., Kypreos S., Barreto L., Wokaun A.: Steps towards the 2000 Watt Society in Switzerland. Energy Technology System Analysis Programme (ETSAP) Workshop, Florence, Italy, 11. November 2004.

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