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Electric Energy System Planning and the

Second Principle of Thermodynamics

by

Delly Oliveira F.

A thesis submitted to the Faculty ofGraduate Studies and Research

in partial fulfilment ofthe requirement for the degree

ofDoctor ofPhilosophy

Department ofElectrical Engineering

McGiIl University

Montréal, Québec, Canada

<0 October 1995

1+1 National Libraryof Canada

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The author retains ownership ofthe copyright in hisjher thesis.Neither the thesis nor substantialextracts from it may be printe;:! orotherwise reproduced withouthisjher permission.

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L'auteur conserve la propriété dudroit d'auteur qui protège sathèse. Ni la thèse ni des extraitssubstantiels de celle-ci nedoivent être imprimés ouautrement reproduits sans sonautorisation.

ISBN 0-612-12452-5

Canada

1.

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Abstract

This thesis deaJs with the long-tenn planning ofe1ectric energy systems. Such systems are

defined by complex interconnections of end-uses, energy conversion devices and natural

resources. The planning process is usually guided by a number of design criteria, namely,

economic, social and environmental impacts as weil as system re1iability and efficiency. The

planning challenge is to find an acceptable compromise among these often conflictive

objectives. System efliciency is a critical design criterion normally measuring the ratio ofthe

system output and input energies. In e1ectric energy systems, efficiency is nonnally defined

according to the First Principle of Thermodynamics which states that energy cannot be

destroyed. In this thesis, the definition ofefficiency in e1ectric energy system planning is

broadened to include interpretations aocording to both the F1I'st and Second Principles of

Thennodynamics. The Second Principle essentially states that the "quality" of energy

decreases or, at best, remains constant in any conversion process where the quality ofenergy

(denoted here by exergy) is a measure ofthe ability ofa fonn ofenergy to be converted into

any other form. Work, hydroelectric potential and e1ectricity are examples ofhigh quaIity

energy sources while low temperature heat end-use applications are at the low end ofthe

quality scale. Since certain types ofenergy conversion processes may show high levels of

excrgy destruction, even though energetically efficient, it is important to design energy

systems such that the energy quality ofan end-use is matched as much as possible to that of

the energy supply thus avoiding situations where a high quality supply is used for a low

quality purpose.

The e1ectric energy industry bas virtually ignoredexergetic considerations in system planning

due, to a large extent, to a Jack offamiliarity with the Second Principle and its implications.

Nevertbeless, exergy is an attn1>ute which must be planned and conserved with at least the

same priority as energy. It is demonstrated here that the planning ofenergy systems will be

drastically affected when both energy and exergy are considered. However, to be able to

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Abstract

rationalIy use the natural resources, exergetic analysis must become an integral part ofsystem

plamüng. This thesis analyses the application ofthe Second Principle ofThermodynamics in

the plamüng ofe1ectric energy systems through theory, examples and case studies including

econonûc considerations.

In order to achieve e1ectric energy systems that are more exergetically efficient, a new type

of electric energy tariffcalled type-of-use. is proposed. Analogous to the time-of-use rate

that assigns different monetary values for the time ofthe day considered, the type-of-use tariff

assigns a monetary value to the end-uses. Simulations are performed in different e1ecuic

energy systems to demonstrate that type-of-use tariffs will indeed lead to more exergetically

efficient system!:.

The benefits of exergetic analysis are supported by a number of studies presented in this

thesis. These studies analyse from the points ofview ofenergetic and exergetic efficiency and

cost the foDowing: (i) A space heating system; (u) The impact ofa major introduction of

e1ectric vehicles in Canada and (Ù!) The long range planning of a regional electric power

system consisting oftwo intercoMeeted provinces.

iii

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Résumé

Cene thèse traite le problème de planification à long tenne des réseaux d'énergie électrique.

De tels réseaux sont définis par des liens complexes entre les utilisations finales de l'énergie,

les appareils de transformation d'énergie et les ressources naturelles. Le processus de

planification s'oriente par divers critères de conception, c'est à dire, l'impact socia

économique et environnementale bien que la fiabilité et l'efficacité. Le défi de la planification

est de trouver un compromis acceptable entre ces objectifs souvent en conflit. L'efficacité du

réseau est un critère vital qui mesure normalement le rapport entre l'énergie totale à l'entrée

du système et celle à la sortie. Dans les réseaux électriques, l'efficacité est typiquement définie

selon le Premier Principe de Thennodynamique qui stipule que l'énergie ne peut pas être

détruite. Dans la thèse présente, la définition d'efficacité dans la planification de réseaux

d'énergie électrique est étendue pour inclure des interprétations selon le Premier bien que le

Deuxième Principe de Thermodynamique. Le Deuxième Principe établie que la "qualité"

d'énergie décroît ou, tout au mieux, se maintien constante dans tous les processus de

conversion d'énergie. La qualité de l'énergie, dénommée exergie, est une mesure de la

capacité d'une forme d'énergie donnée d'être convertie à n'importe quelle autre forme. Le

travail mécanique, le potentiel hydraulique et l'électricité sont des exemples de sources

d'énergie de haute qualité pendant que les applications utilisant de la chaleur à basse

température sont situées très bas dans l'échelle de la qualité de l'énergie. Vue que certains

types de processus de conversion démontrent de forts niveaux de destruction d'exergie,

même s'ils sont efficaces du point de vue de l'énergie, il est important de bâtir les réseaux

d'énergie de telle manière que la qualité de l'énergie des usages finaux so:t compatible autant

que poSSIble avec la qualité des ressources naturelles. De cette façon, des cas sont évités ou

une source de haute qualité est utilisée pour un usage finale de basse qualité.

L'industrie électrique a pratiquement ignoré des considérations exergetiques dans la

planification de réseaux, principalement due à une manque de familiarité avec le Deuxième

iv

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Résumé

Principe et tout ses implications. Néanmoins, l'exergie est un attribut qui doit être planifié et

conservé avec, au moins, la même priorité que l'énergie. Il est démontré ici que la

planification des réseaux électriques sera dramatiquement affectée quand les deux critères

d'énergie et d'exergie sont traités. Cependant, pour pouvoir utiliser d'une façon rationnelle

nos ressources naturelles, l'analyse exergetique doit se convertir dans une partie intégrale du

processus de planification. Cette thèse analyse l'application du Deu.'CÎème Principe de

Thermodynanùque à la planification des réseaux électriques à travers la théorie, des exemples

et des études de cas particuliers incluant des considérations économiques.

Afin d'obtenir des réseaux électriques qui sont plus efficaces exergetiquement, une nouvelle

tarife d'énergie électrique dénommée la tarife type-d'usage est proposée. D'une manière

analogue à la tarife heure-du-jour, qui établie une valeur monétaire de l'énergie électrique

pour chaque période du jour, la tarife type-d'usage établie une valeur monétaire sur les

usages finaux de l'énergie.

Les bénéfices de l'analyse ex:ergetique sont supportés par des études décrites dans cette thèse.

Ces études analysent du points de vue de l'efficacité énergétique et ex:ergetique et

économique ce qui suit: (i) Un système de chauffage résidentiel; (ii) L'impact de

l'introduction des véhicules électriques au Canada; (m) La planification à long terme d'un

réseau régional consistant de deux provinces interconnectées.

v

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Resumo

Esta tese trata do planejamen:o de longo prazo de sistemas de energia elétrica. Tais sistemas

sao projetados de acôrdo corn complexas relaçêies entre 0 uso finaI da energia, aparatos de

conversao e recursos naturais. 0 processo de planejamento é geralmente orientado por um

numero de critérios notadamente: impactos socio-econêmico e ambiental, bem coma a

confiabilidade e eficiência do sistema 0 desafio do planejamento é de se encontrar um

compromisso entre estes objctivos frequentemente conflitivos. A eficiência do sistema é um

critério de planejamento vital e é definido pela raziio entre as energias de saïda e de entrada

Nos sistemas de energia elétrica, eficiência é norma1mente definida de acêrdo corn 0 Primeiro

Principio da Termodinâmica, que estipula que a energia nao pode ser destruida Nesta tese

a definiçiio da eficiência para 0 planejamento de sistemas de energia eletrica é expandido para

inc1uir a interpretaçiio niio somente de acordo corn 0 Primeiro Principio mas também corn 0

Segundo Principio. 0 Segundo Principio da Termodinâmica essencialmente e,;tabelece que

a qualidade da energia decresce ou no me1hor dos casos permanece constante em qualquer

processo de conversao da energia A qualidade da energia, denotada aqui por exergia, é a

capacidade da energia de se converter em qualquer outra forma 0 trabalho mecânico, 0

potencial hidrâu1ico, e a eletricidade sao exemplos de fontes de energia de alta qualidade.

Enqllanto a aplicaçiio da energia a baixa temperatura estiio no fim da escaIa de baixa

qualidade. Visto que, certos tipos de conversao da energia podem ter altos niveis de

destruiçiio da exergia apesar de serem energeticamente eficientes, é importante que se projete

sistemas de energia elétrica de ta! modo que a qua1idade da energia de um dado !ISO finaI seja

compative\, tanto quanto possive\, corn à do suprimento da energia

o setor de energia elétrica tem virtualmente ignorado consideraçêies exergéticas no

planejamento de sistemas devido principalmente a falta de familiaridade corn 0 Segundo

Principio da Termodinâmica e de todas as implicaçêies decorrentes. Antes de mais nada,

vi

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Resumo

exergia é uma grandeza que deve ser considerada no planejamento pelo menos corn a mesma

prioridade da energia. Se demonstra aqui, que 0 planejamento de sistemas elétricos seradramaticamente afutado quando energia e exergia forem considerados. Todavia, para ser

capaz de utiIizar racionamente os recursos naturais, a anâlise exergética deve se tornar uma

parte integrante do processo de planejamento de sistemas de energia e1étricos. Esta tese

analisa a aplicaçao do Segundo Principio da Termodinâmica no planejamento de sistemas de

energia e1étrica através de teoria, exemplos e de estudos de cases particu\ares, incluindo

consideraçOes econômicas.

Afim de alcancar sistemas de energia e1étrica que sejam mais eficientes exergeticamente, um

novo tipo de tarifa de energia, denominada tipo-de-uso, é proposto. Do mesmo modo que a

tarifa hora-do-dia que estabe1ece um valor monetârio para cada um dos interva10s do dia

considerado, a tarifa tipo-de-uso estabeIece umvalor monetârio para os usos finais da energia

considerados. SimnlaçOes sao feitas em diferentes sistemas e1étricos para desmonstrar que a

tarifa tipo-d~uso ira certamente induzir sistemas e1étricos mais eficientes exergeticamente.

Os beneficios da anâIise exergética siio confirmados por um mimera de estudos apresentados

nesta tese. Estes estudos ana1isamdos pontos de vista, da eficiència energética, exergética e

econômico, os seguintes cases: (i) sistemas de aquecimento do ambiente, (ri) 0 impacto da

introduçio de carros e1étricos no Canada e (üi) 0 p1ant<jamento de longo prazo de um sistema

regional de potència consistindo de duas provincias.

vü

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AcknowIedgments

FJIStly, 1would like to thank God through Jesus Christ, because 1really have proven that He

is a great loving Father.

My sincere thanks to Professor Francisco D. Galiana for his knowledgable supervision,

encouragement and warm fiiendship, throughout this research. Without any doubt, 1 can say

that 1had the privilege, to say the least to have been supervised by Professor Galiana.

1 would Iike to thank Professor R Baliga, Professor R Banakar, Professor B. Gevay and

Professor B. T. Ooi for their support during my study.

1am thankful to my fiiends and colleagues in the Power Group. It was a great opportunity

to get to know and share experiences with fiiends with such a rich acadernic and cultural

background. 1 would Iike to thank Lester Loud, John Cheng, Luiz Lopes, Dr. Houssein

Javidi, Djordje Atanackovic, Bakari Mwinyiwiwa, Nivad Navid, George Jaber, Dr. Mherdad

Kazerani. 1 would Iike to thank as weil to the secretaries of the Department ofEleetrical

Engineering ofMcGiII University, Mrs P. Hyland, Mrs. R Pinzarrone and Mrs P. Jorgensen.

1 am very thankful to CAPES (Coordenadoria de Aperfeiçoamento de Pessoa! de Ensino

Superior) and to the FederaI University ofViçosa for the financial support that gave me this

unique opportunity.

1would Iike to thank, as weil, Mrs. E. Woolerton for giving me encouragement and support.

Last but not least, 1would Iike to thank my family, starting with my dear wife Luci for ber

support and incommensurable sacrifices, that aIIowed me to reaIize this objective. Thank you,

Acâcia, Liz and Ivo, you are wonderful children. 1 am blessed to be your failier, thank you

for your love.

viü

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• ix

To

my dear wife Luci

and

our children Acacia, Liz and Ivo

• Table of Contents

Abstract 11

Résumé IV

Resumo vi

Acknowledgments viii

Table of Contents x

List of Tables xv

List ofmustrations xix

Nomenclature xxi

Chapter 1. Introduction 1

1.1 Planning ofEIectric Energy Systems 1

• 1.2 Concepts ofExergy and Exergetic Efficiency 5

1.3 Motivation for Using the Second Principle in 7

EIectric Energy System Planning

1.4 Objectives oftlùs Thesis 9

1.5 Thesis Outline 10

1.6 Claim ofOriginality Il

•

Chapter 2. First and Second Principles ofTbermodynamics

2.1 Energetic and Exergetic Efficiency

2.2 Energy, Exergy and Entropy

Chapter 3. Electric Energy System Model

3.1 Motivation

3.2 Basic System Model

3.3 Mathematical Energy System Model

x

13

13

19

23

23

24

26

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Table of Contents

3.4 Example ofMathematical Model

3.5 Energy System Optimization

3.6 Computer Model

3.7 Concluding Remarks

Chapter 4. Applications of Exergy Analysis in Electric Energy

System Planning

4.1 Introduction

4.2 Linùting Levels ofFPT and SPT Efficiencies

4.3 Demand Side Management Perfonnance Improvement

4.3.1 Basic energy conversion model element

4.3.2 Model with cross-effects

4.3.3 System impact ofDSM perfonnance improvement

strategies description ofcase-studies

4.3.4 Evaluation ofPI measures

4.3.5 Comparison of savings at different system levels

4.3.6 Comparison ofenergetic and exergetic savings

4.3.7 Comparison ofdifferent perfonnance improvement measures

4.3.8 The effeet ofdifferent climates and dwelling insulation levels

4.4 Energetic and Exergetic Impact ofElectric Vehicles in Canada

4.4.1 Introduction

4.4.2 Evaluation ofe1ectric vehicle (EV) and internai combustion

engine vehicle (lCEV) efficiencies

4.4.3 Energy system with EV and ICEV

4.4.4 Petroleum displacement by EV

4.4.5 Energy supply for EV

xi

31

35

42

42

43

43

46

53

54

57

60

62

64

65

66

68

68

68

70

73

80

82

5.1

5.2

5.3

• 5.4

5.5

5.6

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Table of Contents

4.5 Conc1uding Remaries

4.5.1 Limiting IeveIs ofSPT and FPT efficiencies

4.5.2 DSM perfonnance improvement inc1uding cross-effects

and exergetic anaIysis

4.5.3 Electric vehic1es and exergetic analysis

Chapter 5. Economie and Exergetic Optimization Analysis

ofSpace Heating Systems

Introduction

Space Heating Model

Economie Analysis ofSpace Heating

Optimization with Mixed Objectives

Implementation ofDesired Optimum Solutions

Closure

Chapter 6. Exergetic Optimal Regional Planning

6.1 Introduction

6.2 Region Characterization and Model Description

6.2.1 Regional planning model

6.2.2 Estimation ofthe end-uses for Québec and Ontario for 1995

6.2.3 Limiting levels ofFPT and SPT efficiencies

6.3 Regional Planning Optimization Studies

6.3.1 Québec-Ontario 1995 system

6.3.2 Base case constraints for regional planning

6.3.3 Impact oftransmission line capacity

6.3.4 Comparison ofthe 1995 case with the maximum SPT system

xii

87

87

87

88

90

90

92

95

103

113

118

120

120

122

125

129

133

136

139

142

144

148


effieiency solution

6.3.5 Upper bound limits relaxation 152

6.3.6 Exergetie or type-of-use tariffs 154

6.4 Coneluding Remarks 158

Chapter7. Conclusions and Recommendations for Future Research 163

7.1 General Conclusion 163

7.2 Specifie Conclusions 163

7.2.1 Exergetie ana1ysis in the context ofIntegrated Resouree 164

Planning

7.2.2 Deve10pment ofan energetic and exergetie generaI model 165

for the design and ana1ysis of e1ectric energy systems

• 7.2.3 Demonstration ofthe impact ofexergetic considerations 166

on the planning process ofe1ectric energy systems

7.2.4 Integration ofenergetic, exergetic and economic ana1ysis 167

7.2.5 Energetic and exergetic regional optimization studies 168

7.2.6 A proposition ofa new kind ofe1ectric rate, type-of-use 170

tariffs, that incorporate exergetic considerations

7.3 Recommendations for Future Work 171

•

References 173

Appendix A. First and Second Principle Efficiencies for DilTerent System 184

Configurations

Appendix B. Energetic and Exergetic Savings at DilTerent System Levels 187

for DSM Performance Improvement

Appendix C. Estimation of the End-uses for Ontario and Québec in 1995 190

xili


C.I Ontario End-uses 191

C.U Space-heating end-use in Ontario 191

C.1.2 Space-heating end-use in Ontario 192

C.l.3 Water heating end-use in Ontario 193

C.1.4 Lighting end-use in Ontario 193

C.I.S Traction end-use in Ontario 195

C.2 Québec End-uses 196

C.2.l Space heating end-use in Québec 196

C.2.2 Cooking end-use in Québec 196

C.2.3 Water heating end-use in Québec 197

C.2.4 Lighting end-use for Québec in 1995 198

C.2.5 Traction end-use for Québec in 1995 199

•

• xiv

• List of Tables

Table 2.1 F1I'St (Tl) and Second (e) Principles efficiencies and percent exergy 17

in the input (a,) and output (aJ energies.

Table 3.1 Data for the example ofFigure 3.2. 32

Table 3.2 Energetic and exergetic relations for Figure 3.2. 34

Table 3.3 Numerica1 examples ofefficiencies for extxeme design objectives. 37

Table 3.4 Energy and exergy relations as function ofe, and ~. 37

Table 4.1 End-uses, end-uses devices and natura1 resources considered. 45

Table 4.2 Main system configurations. 46

Table 4.3 Main system configurations in decreasing order ofefficiency. 47

Table 4.4 Energy system configurations considered. 60

Table 4.5 Energy and exergy savings at the appliance level. 61

Table 4.6 Energetic savings at different system levels for 62

PI '1mproved Refrigerator'.

• Table 4.7 Exergetic savings at different system levels for 63

PI '1mproved Refrigerator'.

Table 4.8 Use ofthe energy in an typica1 gasoline powered ICEV. 67

Table 4.9 Electric vehicle characteristics. 69

Table 4.10 Forecast fuel consumption (kmIl) and weight (kg) of ICEV. 70

Table 4.11 F1I'St (Tl) and Second (e) Principle efficiencies for ICEV and EV. 71

Table 4.12 Configurations considered for road transportation. 72

Table 4.13 First Principle efficiency for eight configurations for 75

road transportation in 1995.

Table 4.14 FII'St Principle efficiency for eight configurations for 76

road transportation in 2010.

Table 4.15 FII'St and Second Principle efficiencies for 77

ICEV and EV different configurations.

Table 4.16 E1ectric energy production for difi'etent fuel types in Canada, 1992. 78

• Table 4.17 EV efficiencies in the Canadian provinces. 79

xv

• List of Tables

Table 4.18 Pettoleum displacement by the adoption ofEV in 1995 and 2010. 81

Table 4.19 Percent ofelectric energy consumption above the present level 83

due to by EV in the Canadian provinces, in 1995 and 2010.

Table 4.20 Yearly consumption ofspace heating alternatives and 84

electric energy conserved to replace an electric baseboard.

Table 4.21 Savings characteristics to replace electric baseboard heater by 85

more exergetically efficient options in terms ofroad transportation

end-use in 1995 and 2010.

Table 5.1 Relevant economic data for different space heating alternatives. 96

Table 5.2 Average Iife cost.~ to customers for di1ferent space heating alternatives. 100

Table 5.3 Energy, maintenance and capital average costs at the customer 101

Ieve\ for different space heating optiOI:S for Ontario.

• Table 5.4 Energy, maintenance and capital costs at the customer Ieve\ for 101

different space heating options for New York.

Table 5.5 Energy, maintenance and capital costs at the customer Ieve\ for 102

di1ferent space heating options for Québec.

Table 5.6 Best space heating design as a function ofthe minimiZl'tion 103

criterion, unconstrained case.

Table 5.7 Optimizarion criterion and objective function considered for the 104

space heating model analysïs.

Table 5.8 Optimum energy states for di1ferent oprimizarion criteria. 105

Table 5.9 Optimum exergy states for different optimization criteria. 106

Table 5.10 Cast and efficiencies orthe space heating for di1ferent 108

optimum criteria.

Table 5.11 Minimum energy/exergy weights (c/kWh) in the Iinear programming 113

objective to force the solution to be equal to the minimum Xa solution.

• Table 5.12 Minimum % subsidies for varying oPPOrtunity cost rates in the initial 115

xvi

• List of Tables

•

•

Table 5.13

Table 6.1

Table 6.2

Table 6.3

Table 6.4

Table 6.5

Table 6.6

Table 6.7

Table 6.8

Table 6.9

Table 6.10

Table 6.11

Table 6.12

Table 6.13

. Table 6.14

Table 6.15

Table 6.16

Table 6.17

Table AI

capital ofthe heat-pump ground-to-air to induce the minimum

exergy and minimum cost solutions to be identical in Québec.

Heat-pump ground-to-air initial capital subsidy and maximum rate 117

for the minimum solution XRbe the minimum cost solution.

Important supply and load charaeteristics in Québec and Ontario 124

in 1995.

States considered for Québec and Ontario. 126

End-use energy for Québec in 1995. 131

End-use energy for Ontario in 1995. 132

Fraction ofthe e1ectric consumption covered by the regional 133

planning study in %.

Cases Iimiting the values ofthe First Principle efficiency, Tl. 134

Cases limiting the values ofthe Second Principle efficiency, E. 135

Summary ofcases studied in regional planning. 137

Energy and exergy states considered for Québec and Ontario for 1995. 140

Upper bound (base case) state limits considered for regional planning. 143

SPT efficiency, for max E, for increasing values oftransmission 145

line capacity.

SPT efficiency, for max Tl, for increasing values oftransmission line 146

capacity.

Comparison of 1995 and Min xRsolutions in Québec. 149

Comparison of1995 and Min xRsolutions, in Ontario. 150

Lagrange multipliers for seleeted states for minimum exergy. 153

Objective function for exergetic tariffdesign. 155

Summary ofcases studied in regional planning. 157

FPT efficiency, Tl, ofend-use devices for various system 185

xvii

• List of Tables

configurations (%).

TableA2 SPT efficiency, e, ofend-use devices for various system 186

configurations (%).

TableB.l Energetic savings at different sys~em 1~'Vels for PI 'Efficient Electric 188

Water Heater'.

TableB.2 Exergetic savings at different system levels for PI 'Efficient Eectric 188

Water Heater'.

TableB.3 Energetic savings for PI 'Replacement ofIncandescent by Compact 189

Fluorescent Light Bulbs'.

Table BA Exergetic savings for PI 'Replacement ofIncandescent by Compact 189

Fluorescent Light Bulbs'.

TableC.l Energy consumption for the space heating end-use devices in 191

• Ontario, 1995.

TableC.2 Energy consumption for the cooking end-use devices in Ontario, 192

1995.

TableC.3 Energy consumption for the water-heating end-use devices in Ontario, 193

1995.

Table CA Energy consumption for the Iighting end-use devices in Ontario, 1995. 194

TableC.5 Energy consumption for traction end-use devices in Ontario, 1995. 195

TableC.6 Energy consumption for space heating end-use devices in Québec, 196

1995.

TableC.7 Energy consumption for the cooking end-use devices for the residential197

sector in Québec, 1995.

TableC.8 Energy consumption for the water heating end-use devices, for the 197

residential and commercial sectors in Québec, 1995.

TableC.9 Energy consumption for the Iighting end-use in Québec, 1995. 198

Table C.I0 Energy consumption for traction end-use devices in Québec, 1995. 199

• xviii

• List of IHustrations

Figure 1.1 Electric energy system. 2

Figure 1.2 The energy planning challenge - balance ofdesign criteria 4

and perspectives.

Figure 2.1 Basic energy conversion e!ement. 15

Figure 3.1 Composition ofa generai energy system. 25

Figure 3.2 DIustrative example ofelectric power system. 33

Figure 3.3 Feasible region. 39

Figure 3.4 Ftrst and Second Principle efficiencies optimization aspects. 41

Figure 4.1 Space heating mode\. 44

Figure 4.2 Second, E, and First, Tl, Principle efficiencies for the end-use 48

space-heating.


• cooIàng.


water heating.


traction.


Iighting.

Figure 4.7 Energy conversion element. 55

Figure 4.8 typical subsystem containing cross-effects. 58

Figure 4.9 Road transportation mode! for internaI combustion engine. 74

vehicles and e!ectrical vehicles.

Figure 4.10 Two natura! resources and end-uses mode!. 82

Figure 5.1 Space heating mode!. 93

Figure 52 F1t'st, Tl, and Second, E, Principle efficiencies for different lIO

• optimization criterion.

xix

• List of Illustrations

•

•

Figure 5.3

Figure 6.1

Figure 6.2

Cost ofthe space heating for different optimization criteria.

for New York, Ontario and Québec.

Model for regional planning.

Second Principle efficiencies for increasing values of

transmission line limits.

xx

III

121

147

• Nomenclature

ac average cost over the life time

Ac matrix ofenergy states ( Ac E R( mX"l)

A. matrix ofexergy states ( Ax E R( mx'l)

ait end-use device alternative

b set ofupper bound limit

b. veetor ofenergy end-uses ( b. E Rm)

bx veetor ofenergy end-uses ( bx E Rm)

BB electric baseboard heater

BL biomass liquefaetion

BP biomass production

BT biomass transport

• Cu cross-effeet

c cost to the customer

Co cost at the energy conversion device leve1

C cooling end-use

Cl, C2, C3 cooking system configurations

Cl,... C6 energy system configurations

~ consumption ofEV

~CEV consumption ofICEV

CF crude refinery

C; energy conversion device i

CK cooking

CM coalmining

co coal natural resource

Cr consumption ratio ICEV and EV

• CR crude recovery

xxi

• Nomenclature

CT crude transport

d petroleum displacement

D driving distance

D diagonal matrix made up ofthe coefficients 0:'0 (D lE R(UO»

DC direct cooking fumace

DH direct oil space heater

DSM Demand Side Management

DW direct water heating

el input energy

~ output energy

e; energy at state i

EL efficient lighting

• ~ energy losses

!la energy at the natura! resource level

EC energy conversion device

EC e1ectric cooking fumace

EM efficient motor

Eq equivalent gasoline savings

eu; energetic content ofa given end-use i

EUi end-uses i

EV E1ectric Vehic1es

EXAM EXergy Analysis Model

EW electric water heating

f objective function, in the optimization procedure

gs natura! gas resource

GE gas extraction and gathering

GT gas transport• xxii

• Nomenclature

ICEV Internai Combustion Engine Vehicles

IM inefficient motor

IL inefficient lighting

IRP lntegrated Resource Planning

FPT First Principle ofThermodynamics

FT fuel oil transportation

GT gasoline transport

H heating end-use

HL heating load

Hp-aa air-to-air heat pump

Hp-ga ground-to-air heat pump

hy hydro energy resource

• 1 illumination end-use

ic capital cost

IC initial capital cost

1 expected number ofyears in the life ofthe device

LI, L2, L3, L4 lighting system configurations

If load factor

LC present life cost

LR syncrude refinery

LT syncrude transport

m number ofend-uses

m maintenance cost per year as a fraction ofthe initial cost

max(x) maximum value ofx

min(x) minimum value ofx

M electric motors

n number ofequalities constraints• xxiü

• Nomenclature

n number ofhours ofoperation per year

n.. number ofenergy conversion devices

n... number ofend-uses

n.. number ofpower plants

fi,. number ofnatural resources

n,.. number ofrefineries

n.. number ofpower plants

n.r number oftransportation offuel systems

n.t numberofttarurnn~onlines

!InI number oftransportation ofnatura! resources systems

NR natural resources

nu nuclear energy resource

• 01 petroleum natura! resource

ON Ontario

om operation and maintenance costs

p opportunity cost rate

P. pressure at the reference state

P_B power plant biomass

P_C power plant coai

P_G power plant natura! gas

P_H,PP-hy power plant hydre

P_O power plant petroleum

PI performance improvement measure

PP power plant

PP-th thermoelectric power plant

q heat transfer per unit ofmass

Q heat transfer• xxiv

• Nomenclature

QB Québec

1'; electric tariff or fuel rate

R-hy hydro resources

RT refined transport

R-th thermal resources

RE refinery

R; natura! resource i

s expected energy cost esca1ation rate

Sj entropy per unit mass ofthe initial and final states

S entropy ofthe state relative to the reference state

SI, S2... S7, S8 space heating system configurations

S· entropy ofthe thermo-mechanica1 dead state

• SR space heating

SPT Second Principle ofThermodynamics

SSM Supply Side Management

T absolute temperature, in Kelvin

T traction

Tl, T2, TI, T4 traction system configurations

T_l coal transport type 1

T_2 coal transport type 2

To reference temperature, in Kelvin

TI temperature ofthe heat source, in Kelvin

T2 temperature ofthe cold sink, in Kelvin

'ID transmission line and distribution system

TF transportation offuel

TL transmission line

TN transportation ofnatura1 resources

• xxv

• Nomenclature

TR transportation device

U1,2 upper bound limits for states 1 and 2

U internaI energy ofthe state relative to the reference state

u" internaI energy ofthe dead state

V volume ofthe state relative to the reference state

V' volume ofthe thermo-mechanical dead state

wi weighting factors in the objective function

WEV we~htofclectricverucle

W1CF:V weight ofinternai combustion engine verucle

Wr efficiency loss factor

WH water heating

Wl,W2,W3 water heating system configurations

• X exergy

~ exergy content in a chemical process

x.... exergy content in the clectricity

X- exergy content in a gravitational ficld

x... exergy content in the kinetic energy

x..,. exergy content in the Iight

x... exergy content in a thermo-mechanical process

".t exergy destruction per unit ofmass

x.s... exergy destruction

XI input exergy

x2 output exergy

xa exergy at the natura1 resource levcl

X; exergy at state i

X.... exergy losses

• XII; exergetic content ofa given end-use i

xxvi

• Nomenclature

y vector ofenergy and exergy states ( y E R:lm)

() refers to the thermo-mechanica1 dead state ofthe system

et proportion ofa exergy in a given energy source

etl proportion ofexergy in the input energy

~ proportion ofexergy in the output energy

et", proportion ofexergy at the end-use

cr. proportion ofexergy at the naturaI resource

etail proportion ofexergy in oil

cr.-. proportion ofexergy in water

cr.- proportion ofexergy in traction

~ proportion ofexergy in low temperature heat

etail proportion ofexergy in oil

• E Second Principle ofThermodynamics efficiency

e.... maximum exergetic efficiency

En. exergetic efficiency ofa thermoelectric power plant

Elly exergetic efficiency ofa hydroelectric power plant

EM exergetic efficiency ofa electric motor

EDR exergetic efficiency ofa direct oil space heater

EBB exergetic efficiency ofa electric baseboard heater

TI FII'st Principle ofThermodynamics efficiency

TlAC air-conditioning coefficient-of-performance

TJEV electric vehicle efficiency

TlICEV internzl combustion engine vehicle efficiency

TIL lighting alternative efficiency

TlSH space heating device efficiency

TI.... maximum energetic efficiency

• TIn. energetic efficiency ofa thermoelectric power plant

xxvii

•

•

•

Nomenclature

Po,;

ô

energetic efficiency ofa hydroelectric power plant

energetic efficiency ofa e1ectric motor

energetic efficiency ofa direct oil space heater

energetic efficiency ofa e1ectric baseboard heater

Carnot efficiency

subsidy level

variation in a given parameter or variable

chemical potential ofsubstance i at the thermo-mechanical dead state

chemical potential ofthe substance i at the reference state

adjust on the weighting function for the hydro potential natural resource

for optimization purposes

xxviii

•

•

•

Introduction

Chapter 1. Introduction

1.1 Planning of Electric Energy Systems

Electric energy systems form one ofthe most vital components of life-support systems in

modern-day societies. It is therefore essentia1 to he able to plan the best system possible

based on the following genera11y accepted design criteria:

(i) Reliabi1ity,

(ù) Efliciency,

(m) Environmental impact,

(IV) Socioeconomic consequences.

The cha11enge of system planning is to find an appropriate balance among these often

conflieting objectives.

1

•

•

Introduction

•••

•••

• •• •• •C

C.- -,--,-Lqud

Jt - ..tlIl'111 .....lUUIC - aera collvenlo. devlcesEU • OIUI-lIICS

2

•

Figure 1.1 E1ectric energy system.

An electric energy system of the general type shown in Figure 1.1 is composed of the

following three main constituentparts:

(a) Natural energy resources,

(b) Energy conversion processes,

(c) End-uses.

Hydraulic potential, petroleum, coal, nuclear minerais and natural gas are examples of

natural resources. The second set ofconstituent parts consists ofseverallayers ofenergy

conversion, transmission or transportation devices wbile end-uses refer to energy services

(e.g., heating, traction and Iight).

• Introduction 3

•

•

Note that the design of an e1ectrie energy system must also inelude non-e1ectrie energy

conversion devices and their respective supplies since the planning ofelectrie energy systems

cannot he carried out in isolation. This is evident because some end-uses can be supplied from

both electrie and non-e1ectrie energy sources. The methodology of Integrated Resource

Planning (IR.P) bas been deve10ped witll these broad considerations in mind [Rosen et al,

1993, Litchiie1d et al, 1994].

In planning e1ectrie energy systems, the emphasis placed on eaeh ofthe four main planning

criteria bas varied over the years. Today, environmental impact (e.g., toxie emissions from

power plants) bas acquired even greater importance than in the pasto Capital, operational and

maintenance costs have always been and will continue to be a very high priority planning

criterion although the least cost solution must be moderated by acceptable levels of

environmental impact, efficiency and reliability as we1I as job creation and other social impacts

[Northwest, 1991]. In the IRP context, costs may refer to the utility costs or to those borne

by individual customers or by society [Litchiie1d et al, 1994). The reliability criterion is

normally satisfied through certain minimum standards expected by society in terms ofthe

average number ofpower outages per year and their average duration [Endrenyi, 1978). The

reIiabiIity standards demanded by modern societies are very high due to their ever increasing

dependency on a continuous and ample supply ofe1ectrie energy. Before the first oil crises

of the 197CYs, efficiency had a relatively low priority however increasing fue1 and investment

costs have forced planners to place a much greater significance on the efliciency ofindividual

energy conversion components as we11 as that of the e1ectrie energy system as a whole

[Boustead & Hancock, 1979; Talukdar & Ge1Iings 1987]. Ofthe four main planning criteria,

efficiency and reliability are precisely qllantifiab1.e since they are based on we11 supported laws

of physics and statistics. However, environmental and socioeconomie impacts are more

subjective and usua1ly ref1eet the vaIue placed by society and the market on resources,

services and the protection of the environment. The great hurdle to overcome in the

integrated planning process is to obtain a compromise among the four design criteria, a task

• Introduction 4

•

•

Figure 1.2 The energy planning challenge - balance ofdesign criteria and perspectives.

wbich is complicated by the1àct that iliese objectives do not usually coïncide. See Figure 1.2.

Diftèrentpe~ctives can be followed to assess and implement a given planning sttategy,

namely those of

• The utility,

• The customer,

• Society

From the utilitypoint ofview, the broad objectives are to improve the financial performance

• Introduction 5

•

•

as weil as customer and employee relations [Rosen et al., 1990; EPRI, 1993]. Other utility

objectives include the maximum possible use ofits generation and transmission capacity. the

deferral ofgeneration and transmission expansion plans and the reduction ofthe utility's

dependence on critical fuels. In general, the customer is primarily concemed with energy

rates and supply reliability. The society peispectives encompass at least four major objectives:

macro-eeonomie impacts (e.g., job generatio:l, country development and tax-revenue),

regulation oftariffs and reliability indices, country strategie constraints (e.g., reduction of

eritical technology and fuel dependency) and minimization of environment damage

(emissions, waste disposai, land use). Clearly, there exist conflicts among the three points of

view. For example, the cost objectives ofa utility are not synehronized with those ofthe

customer. Similarly, society is extremely interested in the creation ofjobs which may not be

a high priority objective for the uti1ities. The proper balance between these conflicting

perspectives and objectives bas been studied under the umbrella of Integrated Resource

Planning [Rosen et al. 1993; Hobbs et al. 1993].

1.2 Concepts ofExergy and Exergetic Efficiency

The use ofthe Second Principle ofThennodynamics1 is weil estabIished in numerous fields

such as mechanical and chemical engineering [MacGovem, 1990; Wepfer, 1979; KIenke,

1991; Boustead & Hancock, 1979]. Through this approach, efticiency is measured by two

dimensions. That is, not only by the conventional input/output energy balance as defined by

the First Principle but also by a second dimension ofefticiency in terms ofenergy quaIity

1 In the 1840'5Mayer lIIId JouIe sbowcdtbat thermodynamics is IlOt restrictcd oaly ta bcat

transfcr studies but CI1lXlIDpasses olbcr fonDs ofœcrgy. Mee gœcraIly, thermodynamics cm he

intcrpretcd as energydynamics.

• Introduction 6

•

•

denoted here by exergy. Qua1ity in energy conversion can be quantified through exergetic

analysis based on the Second Principle of Thennodynamics [Oliveira & GaIiana, 1995a;

Gardner& Robinson, 1993]. The quantitative analysis ofthe qua\ity ofenergy bas numerous

implications in the design ofe\ectric energy systems as discussed in this article. Note that,

throughout this thesis, the words Law and Principle are used interchangeably.

The tenn exergy, derived from the Greek, is also known as essergy, availability, free energy

and usefuI energy [Wepfer, 1979]. Exergy is usua\Iy interpreted as avai1able worle. Exergy

represents the fraction ofa form ofenergy that can be converted to any other arbitrary form.

This characteristic is ca1led reverstbility.

To clarify the distinction between energy and exergy, it is important to observe that in

energetic analysis the energy in a given source ofenergy can be considered as constant (e.g.,

45,475 kJJkg ofoil, 37,260 kJ/m3 ofnatural gas)[Québec, 1992]. In contrast, the exergetic

content ofa given source ofenergy is the amount ofkJ ofwork that can be extraeted from

this source. Exergy is not only a function of the source of energy but of the existing

technology for the extraction ofworlc from the given source. For example, the exergy in

e\ectricity is deteimin\ld by the most energetica1ly eflicient e\ectric motor presently available.

As another example, the exergy in a heat source bas a theoreticaI upper bound determined by

the ideal Camot efliciency [Klenke, 1991]. Low temperature heat bas a very low exergy

content in contrast to e\ectricity or mechanicaI worlc which bas a high exergetic content since

the)' .::an be more efliciently converted to other forms ofenergy. In essence, the higher the

reversibility ofa form ofenergy, the higher the qua1ity that is assigned to it. In contrast to

energy which can never be destroyed, some amount of exergy is always irreversIbly lost

during any energy conversion process. Simi1arly to energy conservation, it is important to

minimize the irreversible destruction ofthis valuable resource which is exergy.

• Introduction 7

1.3 Motivation for Using the Second frinciple in Electric Energy

System Planning

The significance ofexergetic ana1ysis bas been recognized in thermodynamics since the third

quarter of last century [Maxwell, 1871] and its application in mechanical and industrial

engineering bas received considerable attention [Kaygusuz & Ayhan, 1993; Nieuwlaar, 1993;

K1enke 1991; Boustead & Hancock 1979]. Although exergetic anaIysis bas been practically

ignored in the planning ofe1ectric energy systems [Gardner & Robinson 1993, Oliveira &

GaIiana 1995a], there exist numerous motivations for incorporating the Second Principle into

this planning process:

•

•

(a)

(b)

One ofthe reasons why energy planning government bodies and the e1ectric energy

industry have not paid much attention to Second Principle efficiency is probably due

to a lack of farnj1jarity with its possible implications and impact on the planning

process. In particular, the economic value attributed to e1ectricity is basically

established, regardIess ofits end-use, in terms ofits energy content and the energy

consumed to generate this e1ectricity. This kWh energy content is usually directly

compared with alternative sources ofenergy (e.g., oil, gas) regardIess oftheir type

with no regard for the quality of the energy. Although it is weil recognized that

e1eetricity is a "bigh quality" energy, this quality bas not been explicitly assigned a

quantitative measure and a corresponding monetary value. In some sense, this is

anaIogous ta comparing a Formula 1racing car with an old jalopy ooly because they

both provide transportation. This thesis strongly recommends that a systematic

framework ofplanning methods and policies should be established by industry and

government to account for the quaIity ofenergy in e1ectric system planning.

Traditionally, e1ectric energy systems have been concerned with the kWh consumed

by the customers regardIess ofthe type ofend-use (i.e., the service provided) since

the kWh consumed define the system e1ectric load forecast wbich was the primary

• Introduction 8

•(c)

driving function of the planning process. A more recent trend is to plan systems

according to the end-use requirements rather than on the basis ofthe kWh consumed

to supply such demands [Litchfie1d et al, 1994; Hirst, 1992; Berrie, 1983]. As an

example, an end-use cao be the heating comfort leve1 inside a dwelling which is not

Ilecessarily measured by the e1ectric energy required since this leve1 cao be affected

by the amount ofiItslllation. Simi\arly, the end-use traction needs ofa given industry

are independent ofthe process used to generate this end-use, more eflicient motors

c1early consuming fewer kWh. Second Principle analysis would a1Iow the

classification of end-uses according to quality by measuring and ranking their

exergetic contenf. For example, traction is a very high quality end-use however low

temperature heat would be ranked very 10w on the quality scale.

Another significant advantage ofexergetic analysis is that it permits the comparison

ofdiffèrent types ofenergy conversion processes, even ifthey have identical FJrst

Principle efliciencies, by exarn;ning the Second Principle efliciency.

•

(d) Exergetic analysis provides a means to systematica1ly and quantitatively incorporate

the irreveI'SIbility ofavailable work ioto the design ofenergy systems. Available work

orexergy is a limited resource that must be monitored and conserved at least on an

equaI footing with energy resources since it bas been argued that exergetic efliciency

is a "true" measure of the rational use of energy [Gardner & Robinson, 1993;

Boustead & Hancock, 1979; Oliveira & Galiana, 1995a]. Ignorance ofthe Second

Principle cao r=Jlt in high levels ofexergy destruction which constitutes, to say the

least, a mismanagP.lIlent and waste ofa limited resource.

(e) The consideration ofexergy in e1ectric energy system planning cao be carried out in

2 Nole tbat eveD eod-uses with low exezgy content (e.g.lowtempaature hcating) must be

supplicd. Exergetic ana1ysis would belp te systernatically find the most suitablc cncrgy supply match

for this low qua\ily applicatiOlL

• Introduction 9

•

the context ofIntegrated Resource Planning (IRP). TIùs is a general approach which

places equal emphasis on the planning of resources at the supply side and their

counterparts at the demand side. Exergetic anaIysis would be extremely helpful to

achieve one ofthe more diflicu1t objectives ofIRP which is the rational matching of

resources to end-uses. As an example of this application, resources with low

exergetic content should be matched to low exergy end-uses as much as possible.

1.4 Objectives of this Thesis

The main objective ofthis thesis is to present a system approach for the planning ofelectric

energy systems including a new perspective, namely, the consideration of system efficiency

as measured not onlyby the more commonly used First Principle ofThermodynamics (FPT)

but, aIso, by the Second Principle ofThermodynamics (SPT). It is shown in this thesis that

the extension of the efficiency criterion to include the Second Principle would resu1t in

fundamentaI changes in the way electric energy systems are designed and operated. The

motivation for such a change in design philosophy is further discussed in this thesis together

with its potential advantages and drawbacks.

The specific objectives ofthis thesis are:

(1) To introduce exergetic anaIysis into the planning ofelectric energy systems.

(2) To deveiop a general model to design and analyse electric energy systems from the

points ofview ofenergetic and exergetic anaIysis;

•(3) To demonstrate through a number of case studies the impact of exergetic

considerations on the planning process ofelectric energy systems;

• Introduction

(4) To integrate economic, energetic and exergetic analysïs in the planning process;

10

•

•

(5) To carry out a regional planning study by optimizing the system energetic and

exergetic efficiencies;

(6) To introduce a type of electric tariff that induces the optimjzation of the use of

naturaI resources from the point-ofview ofthe Second Principle ofThermodynamics.

1.5 Thesis Oudine

Chapter 2 reviews the F11'St and Second Principles ofThermodynamics and presents some

basic data about the FPT and SPT efficiencies ofa number ofend-uses devices.

Chapter3 presents the electric energy system model utilized in the present thesis. The model

accounts for inputs and outputs as weil as internal t10ws ofboth energy and exergy. An

example10 graphically iDustrate the various aspects ofsystem planning from the F11'St and the

Second Principle is presented.

Chapter 4 examines ditrerent applications ofthe Second Principle to electric energy system

planning In the first place, the five most common end-uses, that is, space beating, cooking,

water beating, traction and Iighting are ana\ysed. This study involved 54 diffetent system

configurations including the following naturaI resources: hydrau1ic potential, nuclear energy,

coaI, petroleum and naturaI gas. For each end-use, the lirniting levets ofthe system efficiency

as measured by the F11'St and the Second Principle are calcu\ated. The nela application is the

el' Bllljllarion cfthe impact ofDemand SideManagementPetformance Improvement measures

at the residential sector. The influence ofthe beat-gains due to cross-eff'ects on beating and

coo1ing loads is ïnvestigated as weil. Fma11y, a simulation ofthe impact ofa major adoption

• Introduction 11

•

•

ofelectric vehicles (EV) in Canada is presented. Different aspects are investigated such as:

petroleum disp\acement by EV and possible sources ofenergy to supply the EV alternative.

OptirniZlltion and exergetic anaIysis ofspace heating systems is presented in Chapter 5. T1üs

chapter applies the principles developed in Chapter 3 in greater detail to a more realistic space

heating problem. Mmùm!I!! energy and exergy solutions are compared with the minimum cost

solution. Diffi:J:ent types ofcost incentives are analysed in order that the minimum exergetic

solution be adopted by the customers. This includes subsidies in the capital cost, in the

opportunity cost rate, or in the electric rate. The analysis is performed for three regions in

North America, tbat is, New York, Québec and Ontario.

Chapter 6 presents a study ofthe planning ofelectric energy systems at the regional leve\

including exergetic considerations. The region studied is composed ofthe Canadian provinces

of Québec and Ontario. First and Second Principle analyses are performed simulating the

influence of different values of transmission line leve\s connecting the two neighbouring

provinces as weil as the state constraints. A different type oftariff structure is introduced

based on the type-oj-use ofenergy. This tariffstructure is tested in order to induce the system

to maximize its ex:ergetic efliciency.

Fmally, Chapter 7 presents the conclusions of the present thesis together with

recommendations made regarding future work.

1.6 CIaim ofOriginality

This thesis proposes tbat energetic analysis derived from the Second Principle of

Thermodynamics should become an integral part ofthe planning ofe\ectric energy systems.

• Introduction 12

•

•

Energetic analysis is specialIy important to ensure a rational matching ofnatura! resources and

end-uses ofenergy, in o'.her words, that high quality energies be used for quality end-uses to

the extent feasible. Energetic anaIysis is a type ofanaIysis, which at present, is not explicitly

considered in the e1ectric energy system planning.

The benefits of exergetic anaIysis are supported by a number of studies presented in this

thesis. These studies analyse from the points ofview ofenergetic and exergetic efficiency and

cost the following: (i) A space heating system; (ul The impact ofa major introduction of

e1ectric vehicles in Canada and (ml The long range planning of a regional e1ectric power

system consisting oftwo interconnected provinces.

A new type ofe1ectric energy tariffis proposed ca1Ied type-oj-use. This tariff is analogons to

the time-of-use rate but it assigns a monetaIy value to the end-use according to the type of

services provided. The purpose ofwhich is to induce the system to maximize the efficiency

as measured by the Second Principle ofThermodynamics. A number ofoptimi'Zlltion studies

are presented in this thesis to support the hypothesis that type-oj-use tariffs willlead to a

more exergetica1ly efficient use ofenergy.

•

•

First and Second Principles of Thermodynamics

Chapter 2.

First and Second Principles of Thermodynamics

2.1 Energetic and Exergetic Efficiency

The understanding ofthe energetic and exergetic analysis and the corresponding efficiencies

are presented in this section. Exergetic analysis is a technique at the forefront ofapplied

thermodynamics research where any systems that uti1i2.e energy are assessed in the Iigbt ofthe

Second Law of Thermodynamics. AlI forms of energy transfer and transport can be

represented by equivalent exergytransfers which are, in filet, the quantities ofwork that could

be produced ftom the same types ofenergy transfer [McGovem, 1990a].

The FII'St Principle ofThermodynamics (FPT) states that energy con neither he crealeDnor

destroyed but con only he cJv:mgedfrom oneform to another [KIenke, 1991; Bejan, 1988;

Holman, 1980 ]. Thus, for any energy conversion process,

13

• First and Second Principles of Thermodynamics

[Input Energy] = [UsefuI Energy] + [Losses]

The energetic efficiency ofa process based on the FPT is defined as,

,,= UsejuI EnergyInput Energy

14

(2.1)

(2.2)

•

The Second Principle ofThermodynamics (SPl) states tbat heat cannot be directly converted

to work without any other effect. For a heat engine, low temperature waste heat cannot he

avoided [Krenz, 1980, Eejan, 1988; Holman, 1980]. In other words SPT states that during

any energy transformation, the quaIity ofthe energy. as measuredby ilS ability toperjorm

work (erergy) degraJies orat most keeps ilS original state.

[Exergy (Input Energy)] ~ [Exergy (UsefuI Energy)] + [Exergy (Lasses)] (2.3)

It is evident from the above inequality that, un1ike energy, exergy is not conserved in a

process. The destruction ofelœlgy is caned irTeversibiIity. Note the c1ear distinction between

lasses and the irreversible destruction ofexergy. Lasses are energy which is not usefùI to the

particular conversion process and it is usua11y in the form oflow temperature heat. Energy

losses do not however imply a destruction, simply a conversion to another non usefùI form

of energyl. On the other band, the destruction ofexergy in an energy conversion process

normally implies a permanent decrease in the amount ofavailable work.

1 There exist numerous examples of energy losses with usefùI applications such as

• cogeneration [perlman & Moore, 1991, Clark, 1986] and space heating "heat gains" due

to cross-efftcts [Moreau & Stricker, 1994].


Encrgy , Exergy in the 1.osses

IS

InputEncrgy , Exergy

e,

xLou Lou

Useful Encrgy

e, ~onvc:rsion.,

ent -,x, t1,€ x,

,Exergy Destructionx....

,Exergy

•

Figure 2.1 Basic energy conversion e1ement.

The energetic efficiency ofa process based on the SPT is given by,

t: = Exergy (Useful Energy)Exergy (Input Energy)

(2.4)

•

Figure 2.1 illustrates these two Principles in tenns ofthe energy and exergy variables ofa

basic energy conversion e1ement. Note that this device bas one input and three outputs. The

input bas two attributes or dimensions, the energy and the exergy. Simi\arly, the useful output

and the lasses output also have two such atttibutes. The third output, bas only one attribute,

name1y the exergy destruction since by the Fust Principle no energy destruction can occur.

In many energy conversion devices, the losses consist ofiow temperature heat 50 that its

exergy content, "'- is re1atively low. In such cases the exergy destruction, x.- can be

accurate1y estimated by X:z - X, = (1 - e) x,,

In this study, the function Exergy(.) re1aring energy and cxcrgy is cxpresscd by,


Erergy = a Energy

16

(2.5)

where a is a parameter lying between zero and one dependent on other states such as

temperature in the case of heat as weil as on the available technology for converting that

particular form ofenergy into work. A justification and examples ofrelation (2.5) is given

below. From equations (2.2), (2.4) and (2.5), it follows that for a given device,

(2.6)

•where al and ~ are the a's corresponding to the input and output sources of energy

respectively. This is an important equation indicating that the First and Second Principle

et1iciencies and the energy/exergy conversion factors are not independent.

In the case ofheat, ais limited by the Carnot et1iciency ofthe ideal heat engine cycle, TIc..

and depends on the temperatures ofthe heat source, T:z, and ofthe cold sink, Tl, and the

reference temperature T. that is,

1'Jcœ- = 1 (2.7)

where, 8SS'!1l1ing a finite heat source and sink, T is the logarithmic average ofthe cold and hot

sources [McGovern, 199Oa],

• T = (Tl - Tz)ln (TIl T.J

(2.8)

• First and Second Principles of Thermodynamics 17

Table 2.1 First (11) and Second (e) Principles efficiencies and percent exergy in the input

1] for lIIl" CODditiomng aDd hcat.pumps IS the roef!iaeut-of-peâClnllllllCe.

a,) and output (a:.,) enenties.

Encrgy Conversion DevieeParamcler (%)

t].

€ Ct, ex,1. Natural Rcsourcc Tl'llIlSpOl"Ultion 99.0 99.0 37.0 37.0

2. Rdincry 95.0 85.5 41.1 37.0

3. Power-plant

3.1. Hyclro Power-plant 95.0 93.0 97.0 95.0

3.2. ThcnDlÙ Power-plant 35.0 89.9 37.0 95.0

4. Transmigsjoo and Distribution 90.0 89.4 95.0 94.4

5. Fuel Transportation 94.0 72.0 37.0 28.3

6. Spacc Heating (0 to 20" C)

6.1. Electric Basc-board 100.0 2.8 95.0 2.7

6.2. Heat -pump Air-to-aïr 170.0 4.8 95.0 2.7

6.3. Heat-pump Ground-to-8Ïr 300.0 8.5 95.0 2.7

6.4. Di=! OiIIGas Spacc Heating 81.0 5.9 37.0 2.7

7. Water Heating (10 to 60" C)

7.1 StandardElectric Water Heatcr 82.0 5.2 95.0 6.0

7.2. Di=! OiIIGas _ Heatcr 80.0 13.0 37.0 6.0

S. CmkiDgdcviccs(20to ISO"C)

S.1. Electric CookiDg Deviee 89.0 11.5 95.0 12.3

S.2. Di=! OiIIGas CooIcing Deviee 70.0 23.3 37.0 12.3

9. Air ConditiODÏDg (32 to IS OC) 300.0 5.7 95.0 I.S

10.1. ElectricMotor (0.25 kW)

10.1.1 Standard 5S.0 61.1 95.0 100.0

10.1.2. Efficient 69.5 73.2 95.0 100.0

10.2. Electricmotor (10 kW)

10.2.1. Standard 85.0 89.5 95.0 100.0

10.2.1. Efficient 87.4 92.0 95.0 100.0

11. Ligbt

11.1. Jucandesœut 5.0 0.2 95.0 3.0

11.2.1"' Fluorescent 20.0 4.2 95.0 20.0. . .. . . .

•

•


•

Note that, for practical reasons, the ideal Carnot efficiency cannot he achieved but can only

be considered as an upper bound Iimit.

As examples ofthe above-mentioned ideas, the exergy content ofe1ectricity depends on the

efficiency ofthe best e1ectric motor available for the given kW rating (typicaIly in the range

0.80 < Tl < 0.95). Thus, for a 1kW baseboard space heater, where the input is e1ectricity and

the output is heat at 20 degrees C, acloclricily is approximately 95% (based on the highest

efficiencyofelectricmotors) while ac..... is 6.8% (based on the ideal Carnot cycle efficiency

with temperatures of 20 and 0 degrees C). Since an e1ectric baseboard heater is 100"/0

energetically efficient, its exergetic efficiency (e) is 100*6.8/95=7.2%. Therefore, whereas

100"/0 ofthe input energy is converted to a usefuI output in the form ofheat, 92.8% ofthe

input exergy is destroyed by this process. This is a c1ear example of the possible wide

disaepancies between energetic and exergetic efficiencies and ofthe significant irreversible

loss ofexergy even for a process which is 100"/0 energetically efficient [McGovern 1990a;

Krenz, 1980; Klenke, 1991; Oliveira & GaIiana, 1995a).

Comparison between energetic and exergetic analysis guides us to the following reasoning:

To perform energetic ana1ysis ofa process, it is l'ecessary to treat it only as a black box with

known input and output energies but knowledge ofthe process it is not required. On the

other band, to perform exergetic ana1ysis it is l'ecessary to know, not only the input and

output energies, but aIso the details ofthe process as well as the technologies available to

convert the input and output energy into work.

Table 2.1 shows, for a set ofenergy conversion devices, typical values ofthe efficiencies

according to the FD'St and Second Principles ofThermodynamics (Tl, e) as well as the fraction

ofthe input (aJ and output (~) energy that can he converted to work. In this Table, the a's

are estimated assnming the most efficient available technology to convert a given form of

• energy into available work [Wang & DeLuchi, 1992; Québec, 1992a,b,c; Zhu& Lodola,

1993, Law, 1993; Hydro-Québec, 1993].


For an energy system with multiple natural resources, R; , and multiple end-uses, EUj , the

F1I'St and Second Principle efliciencies are defined as follows:

n.

E EU,

" =/-1

(2.9)n,

E Rjj-1

•(2.10)

2.2 Energy, Exergy and Entropy

In tbis section the relationsbip among energy, exergy and entropy is discussed. While the

FIISt Principle ofThennodynamics is regarded as the principle ofcooservation ofenergy, the

Second Principle is tbat ofirreversibility [KIenke, 1991]. The concept ofenergy is govemecl

by the FIISt Principle but exergy and entropy are regulated by the Second Principle of

Thermodynamics.

• The exergy assocïated with some forms ofenergy is given by straightforward relations:


• Potential gravitational energy is ful)y convertible to worle, thus it is pure exergy,

• Kinetic energy is ful)y convertible to worle, thus it is pure exergy

20

• The chemica1 exergy is the maximum useful worlc that could be produced by the

interaction ofthe system with the reference environment,

• The exergy, X, ofa heat trllnsfer process is given by applying equation (2.11),where

1'). is given by equations (2.7) and (2.8) ifthe idea1 Carnot efficiency is considered,

(2.11)

•l'hus, exergy is, in some idea1 cases, equaI to energybut, in general, exergy is only a fraction

(lX) ofenergy as shown in equadon (2.5).

Exergy can aIso be related to other thermodynamic quantities such as entropy and internai

energy. However, the physica1 significance ofentropy bas historica1ly been the subject of

controversy and is more diflicu1t to conceptualize [Wepfer, 1979]. Whereas entropy tends

to increase to a maximum in any ïsolated system, exergy follows an opposite trend a1ways

tending ta decrease. Exergy is conserved only in idea1 processes which are thermodynamica1ly

reversible. In such processes entropy remajns constant [McGovem, 1990a].

There is agreement in the literature [McGovem, 199Oa; Klenlce, 1991; Wepfer, 1979] that the

total exergy, X, ofa simple substance is given by,

x =X... + Xc:/r + X"... + X.tvr + X., + XUg'" + ... (2.12)

where the subsaipts tin, ch, gray, kin, dec and ligbt respectively represent the exergy content

in thermo-mechanical, chemica1 and gravitational potential, and kinetic, dectrical, and Iight

energies and where the fust two terms are given by,

•

•

First and Second Principles of Thennodynamics

x"" = U - U· - To (S - S') + Po (V - V')

Here,

() refers to the thenno-mechanical dead state ofthe system,

U represents the internaI energy ofthe state relative to the reference state,

S is the entropy ofthe state relative to the reference state,

V is the volume ofthe state relative to the reference state,

iii is the chemical potentia1 ofsubstance i,

N is the number ofmoles ofa specifie substance i,

P. is the pressure at the reference state.

21

(2.13)

(2.14)

The exergy destruction per unit ofmass, x.t. also called irreversibility or the lost work, is

givenby the product ofT. and the entropy generated within the system [McGovem, 1990a).

(2.15)

•

here Ta is the absolute tempeiature ofthe refaence state, ~ , i = 1,2 are the entropies per unit

mass ofthe initia1 and fina1 states, q is the heat transfer per unit mass and T is temperature.

• First and Second Principles of Thennodynamics 22

•

•

In SWllIIIaI)', this section bas higlùighted some ofthe important re1ationships among exergy,

energy, entropy and other thermodynamic properties. In particular, exergy bas a close relation

ta entropy but the former is easier ta conceptualize as it is a measure ofavailable wade.

•

•

•

Electric Energy System Model

Chapter 3.

EIectric Energy System ModeI

3.1 Motivation

An essential component ofelectric energy system planning is to have a clear understanding

ofthe behaviour ofail energy conversion processes from the natura1 resources to the end

uses. This understanding can he gained from the general system mode! shown in Figure 3.1

composed ofinterconnected individual input/output models ofthe type shown in Figure 2.1,

where both energy and eltergy are modelIed. The principal reasons for the deve!opment ofthis

mode! areto:

(a) Provide f1exibility to study and design a broad spectrum ofe!ectric energy

system scenarios of varying size and complexity through a user-fiiendly

software environment,

(b) Sïmulate system planning scenarios based on energy, exergy and cost,

23

• Electric Energy System Model

(c) Optimize system designs.

3.2 Basic System Model

24

•

•

The basic mode! desa:ibing l' geùera1 interconnection among the three main constituent parts

ofan e!ectric energy system (natural resources, energy conversion processes and end-uses)

was shown in Figure 3.1.

Figure 3.1 descn1>es the general model developed for an arbitrary energy system in its full

detail. Severa! forms of natural =urces (NR) cau be considered in the model such as

hydroelectric, nuclear fuel, natural sas. coal, crude oil and solar energy. These resources feed

the different kinds of retineries (RE) or fuel processing plants which, in tum, supply the

electric power plants (PP) or the fuel distribution system (TF). As seen in Figure 3.1, certain

types ofnatural resources (e.g., hydro, solar, wind) directly supply power plants bypassing

the transportation (TN) and fuel processing levels. Power plants provide electricity to the

transmission system (11..) which is connected to the various types of electric energy

conversion (EC) devices (e.g., electric motors, lighting, heating, transportation,

communications, e!ectronics). SimiIarly, the fuel distn"bution systems are tied to non-e1ectric

energy conversion (EC) equipment (e.g., direct space heating, industrial processes,

transportatioc).

The mode! pel11ùts the classification ofenergy conversion devices into more refined classes

For example, one cau difl'erentiate among various types of space beating systems (e.g.,

electric basebosrd, air-to-air heat pump, central oil-fired furnace) or lighting (e.g.,

incandescent, fluorescent). Fmal1y, an of these devices supply the end-uses which are

considered the independent variables ofthe mode! [Broehl, 1987].

•

•


Figure 3.1 Composition ofa general energy systeI!1.

Lqud

NIl - ll&lUrII n:soun:c

'IN -lrIIlSpOIlIlioD oClIIlIIrI1 n:soun:c

RB - "'CIOCI)'

pp - power plaDt

TL -uaasmlssioa Ilae

...

. ..

25

•

The main end-uses incIude traction, Iigbting and heating which can be further subdivided into

more specifie categories as desired or as the available data permits. For example, the heating

end-use can be divided into: spaœ heating, cooking, water heating and ironing. End-uses can

also be classified by sectors (residential, commercial, industrial or institutional). The

definition ofan end-use is very flexible and includes examples such as:

(i) The spaee-heating load ofa region;

(u) The luminosity provided by the high-pressure sodium street Iighting ofa city;


(Iii) Traction requirements in the steel industry.

26

•

•

The term end-use does not descnoe the kWh consumed by the 1000 but, rather, its usefu1

output or its service. For example, the lighting end-use requirements ofa city are elCpressed

in equivalent Joules of lumens.

One drawback ofthis definition ofend-use is that data in this format is not always easily

avai1able and may need to be estimared It is also difficult at times to define or quantllY what

is an end-;.JSe. For example, in space heating or cooling, the comfort level can be considered

as the end-use a quantity which is normal1y measured in terms ambient temperature and

humidity and is strong1y affected by the inslllatiQn level ofthe dwelling. The amount ofenergy

needed to meet this comfort level is the input to the model and must be calcu1ated based on

the knowledge ofthe external and internal ambient conditions. Thus, it can be said that no

demand exists for energy itselfbut oniy for the end-use services that it provides [Gardner &

Robinson, 1993; Rab~ 1991]. In spite ofthe difficulties in defining and estimating end-uses,

this is an essential step to be able to systematically plan electric energy systems.

Note that in Figure 3.1, a horizontal bar aets as a "dispatching centre" taking the inputs and

distributing them among its outputs according to a specified distnoution scheme. For

example, the barunder the refineries (RE) takes the refined fuels (e.g., oil, nuclear fuel, gas)

and dispatches some proportion ofeach fuel either to the power plants (PP) or to the fuel

transportation and distnoution system (TF).

3.3 Mathematical Energy System Mode!

Resources, eneIBY conversion processes and end-uses, are subject to equality and inequality


constraints charaeterizing:

(a) Balance ofenergy flow;

(b) Specified end-nses;

(c) Relation between energy and ex:ergy;

27

•

(d) Limits on inputs/outputs of energy conversion, transportation and

transmission processes;

(e) Limits on natural resources;

(f) Government regulations on energy use and environmental impact;

(g) Penetration rates of demaI:d-side management alternatives [Talukdar &

Gellings, 1987; Lithchfie!d et al, 1994];

(h) Costs and tariffs at alllevels;

(i) Constraints imposed by public concems.

Ifthe total set ofattributes (states) ofa given energy system is denoted by a n-dimensional

veetor r. then the mode! for the entir., system is ex:pressed by a linear transfonnation,

where A is a matrix ofdimension m by n with m< n. The m-dimensional veetor b is usually

defined by the specified end-uses. In addition, some or all of the states may he bounded

according to•

•

Ay=b

ymID :S: Y :S: YIIIU

(3.1)

(3.2)

• Electric Energy System Model 28

The system states denoted by the vector y inc1ude energy, exergy and cost variables at all

levels ofthe energy system. The mode! is primarily designed to describe energy and exergy

consumption over a specified time interval (e.g., 1-25 years) as wel1 as the associated costs.

Other system characteristics such as peak load can aIso be modelled given load fàctor

parameters. In addition, the mode! is normally provided with a set of parameters which

inc1ude FII"st and Second Principle efliciencies for all individual devices, capital and

operational cost data, power ratings as wel1 as the limits on all states.

To illustrate the above general mode!, consider a special case where the vector y can he

expressed as,

• y = [elxJ

(3.3)

where e and x represent the vectors ofenergy and exergy states respective!y. Other states

associated with cost may aIso be included. Equation (3.1) then takes the form,

(3.4)

•

and

(3.5)

where the matrixA. depends on1y on the energy network topology and on the FII"st Principle

efliciencies, the matrix A,; depends oDly on the energy network topology and on the Second


Principle efliciencies, while the vector b. depends onIy on the specified energy end-uses.

FinaIly, the vector b. depends onIy on the specified exergy end-uses.

In addition, because ofequation (2.5) re!ating exergy to energy, one bas a set ofrelations of

theform,

x=De (3.6)

•

where D is a diagonal matrix, made up of the coeflicients lXt reIating energy to exergy

examples ofwbich appear in Table 2.1. This type ofgeneral matrix mode! is used extensive!y

in chapter 4 where severa! cases ofsystem planning are exarnjned as weIl as in Chapters 5 and

6 where the optimal design ofenergy systems are discussed.

It is important to note that ofthe three reIations describing the energy/exergy system (3.4),

(3.5) and (3.6), only two are independent, the third being dependent on the other two. Thus

nonnal1y, one only needs the energy reIations (3.4) and (3.6) or equivalently, (3.5) and (3.6).

In order to demonstrate this property, first note that the topologies ofthe energy and exergy

relations (3.4) and (3.5) are identical, only differing in the parameter values as follows:

(i) For each energy conversion device similar to that shown in Figure 2.1 one bas the

reIation,

(3.7)

•appearing in 3.5. However, from 3.6, it follows that,

(3.8)


andthat,

50 that using (2.6),

30

(3.9)

which is the corresponding relation in (3.4).

(3.10)

(ù) At each junction point in the energy networle, the energies and exergies being

summed must be ofthe same type. In such a case, equation (3.4) would contain an

• equation ofthe type,

(3.11)

where n is the number ofenergy f10ws at that junction. Then, using (3.6),

(3.12)

5Othat,

• but since the CXt • s are ail equal at a junction,

(3.13)


(3.14)

•

•

Thus, the energy equation (3.4) together with (3.6) are sufficient tO define the corresponding

exergy equation (3.5).

Thus, to snmmarize this section, it is ooly necessary to develop the energy (exergy) mode) of

the system. The exergy (energy) attributes can then always be obtained from the energy

(exergy) attributes and the relations between energy and exergy (3.6).

3.4 Example of Mathematical Model

In arder ta better understand the generaI mathematical model descn"bed in the previous

section, consider the iIlustrative case shawn in Figure 3.2. This system bas the foUowing

characteristics:

(a) The inputs are the end-uses, in this case, the traelion, T, and the heating requirements,

Q, bath ofwhich are taken as specified quantities;

(b) The heating end-use tan be met by either direct ail heating, DB, or by electric

baseboards, BB;

(c) AIl the traction requirements, T, are met by electric motors;

(d) The electricitY demand is met by thermal (pP-th) and hydro (pP-hy) power plants;

(e) The natura1 resources considered in this simple example are hydraulic potential

(Water, ~o> and crude ail (Oïl, ~J.


Table 3.1 Data for the example ofFigure 3.2.

32

Q = 200 MJouies

11 n = 35 %

1111y= 95%

11M = 87%

11D11= 80%

11BB= 100%

T = 100 MJouies

En = 90% ŒaiI =0.40

EIIy= 93% Œ..- =0.95

EM= 92% Œ_=1.00

EDII =6% Œ_ = 0.027

E 8B =3% 1Iœu.iàl) - 0.95

•(f) The rl1'St and Second Principle efliciencies ofthe five energy conversion devices are

denoted by the symbols 11 and E with the appropriate subscript while the Œ'S represent

the enet13/exergy conversion fàctors. Table 3.1 shows seme typical values assumed

for the example ofFigure 3.2.

For the above mode!, the relations shown in Table 3.2 define the vector equation (3.4).

Then,A. and b. take the form,


T o o o o o o (3.16)

where the superscript T in equation (3.16) stands for the transpose of the vector. These

arrays are normally very sparse, a faet that can be exploited to simplify numerica1 analysis.

T

Q

~

DH..1 e HUI,e4

JJJ

e,PP-th

.. et ~,1

, ,ïl,O

~ BB .. ~,1

,

e. e.eJ' .., pp-,]

J,

410, JY e, T,Gdio",

Jes, M ,

e,

o•

Legeru1

PP-th = tierlfUl1powerpllutbPP-lly =i]tIro powerpllutbDH =lÜredoiZ,plICe1,utenBB =e1edric 6ueiolll'ti iutenM = e1ecIric "'olon

F"JgUre 3.2 IDustrative example ofe\ectric energy system.


Table 3.2 Energetic and exergetic relations for Figure 3.2.

34

Energy Relations Exergy Relations

Q=e l+e 2 "QQ=X 1+X 2

T=e3 T =x3

e.= e I/'I'J OH X.=X 1/E DH

e 5=e2/ 'l'JBB X5=~/ EBB

e6= e3/ 'l'J M X6=X3/ EM

~+el=e5+e6 x,+X I =X 5+x 6

en =e,+e. Xn =x,+x.

eIO=el/'l'JHl' X10= x 1/ E Hl'

e,= e,/ 'l'J 1Il X,=X,/E lIl

• It is also crucial for the mode! to ensure that ail the energy and exergy states are nonnegative

in order to guarantee physically realjz.able solutions.

For the simple iIIustrative system shown in Figure 3.2 the Fust Principle efliciency ofthe

overalI system, 'l'J. is given by.

(3.17)

•whieb is an exampleofthe general equation (equation (22» descn"bing the ratio ofthe total

energy output (sum ofthe end-uses) to the total energy input (sum ofnatural resources).


Similarly the efliciency, E as measured by the Second Principle is given by,

35

E = (3.18)

•

3.5 Energy System Optimization

This simple example serves to iIIustrate the large differences that arise in system planning

when the efliciency criterion is based on the FU'St or on the Second Principles. For example,

two extleme designs can he considered, one that maximizes 1'1 and another that maximize E•

In thefirst design, by anaIysing the energy equations in Table 3.2 as weil as equation (3.17)

and the energy inequalities, as will he demonstrated later in this section, it can be readily

shown that the maximum FU'St Principle efliciency occurs under the following conditions:

• No direct oil heating, that is, 100"10 e1ec:tric baseboard heating.

• No thermal power plant, that is, 100"10 hydroe1ec:tric generation.

This optimum solution is reasonable since, from the FU'St Principle, baseboard e1ec:tric heating

is 100% efficient compared to direct heating (81%), while thermal generation is more

ineflicient (35%) than hydro (95%). This optimum design then yields a FU'St Principle

efliciency given by,

•1'I1IlIX =

Q+TQ T 1'IHy-+-1'188 1'Iu

(3.19)


•

At the other extre:me, ifthe system were designed to maximize the Secontl Principle efliciency

as defined by equation (3.18), again, as will he shown later in this sec, the corresponding

design would he characterized by:

• No electric baseboard heating, that is, 100"/0 direct oil heating.

• No thermal power plant, that is, 100"/0 hydroelectric generation.

Thus, both the First and Second Principle criteria produce designs which exclude

thermoelectric generation. The Second Principle, however, tends to reduce electric

baseboard heating to a minimum replacing it with direct oil heating, in contrast to the First

Principle criterion which does the opposite.

The maximum E design thl::1 :tas a Second Principle efliciency given by,

(3.20)

•

It is also usefùl to e-BIIiÏIICthe design corresponding to the worst efliciencies from the points

ofview ofboth the F1ISt and Second Principles. This design is defined by,

• 100 % thermoelectric generation.

• No direct oil heating, that is, 100% electric baseboard.

Table 3.3 shows the values of" and E for the three ex:tIeme designs describe above.

In SllmmBry, one can observe that system design based on the maximization ofthe F1ISt

Principle efliciency does not necessarily match those designs based on the maximization of


Table 3.3 Numerical examples ofefliciencies for extIeme design objectives.

Design objective Tl (%) e(%)

1. MaYÏmjze First Principle Efliciency 90.6 32.5

2. Maximize Second Principle Efliciency 81.7 50.6

3. Minimize First & Second Principle33.4 31.4

Efliciency

37

•

the Second Principle. In fàct, for this simple example, the maximum Tl design corresponds

to a design close to the minimum e design (31.4%). On the other band, the design

correspondingtothemaximum e (50.6%) bas a corresponding Tl (81.10/0) fàirIy close to its

maximum (90.6%). l'hus, it is poSSIble to find reasonable compromises between the First and

Second Principle requirements.

In order to demonstrate the above optimiZllrion results and to gain greater insight into the

oprimization ofenergy systems, it is worthwhiIe to develop a geometric interpretation ofthe

Table 3.4 Energy and ex:ergy relations as funetion of~ and ~.

•

Energy Relations

~=Q-Ct

e,=T

e.=Ct/1Jœ

e, =(Q - Ct) 11'\aa

~=T lT]w

es =(Q - Ct) IT] B8+T 11'Jw - e,

~ae,/T]m

Ct. '" «Q - Ct) IT] B8 + T hJw -e, ) IT] I!>'

Ctl =el/1Jœ+e,/1'Jn

Exergy Relations

Xs=(~Q-xl)/EB8

x.s=~T/ew

,,"=(~Q-xl)/E88+~T IEw-X,

",,-x,I Em

XI.-«~Q-Xt)/EB8+~T1Ew-x,)1 El!>'

XII "'XI IEœ+X, 1en.


optimization process. Since this system is characterized by Il states and 9 equations (see

Table 3.2), it bas two degrees offreedom which can be independently designed to minimize

or maximize a given objective. These degrees offreedom are not unique, but one possible

choice is the pair (~ and ~), namely, the a......ount of space heating provided by direct

heating, and the output ofthe thermal power plant respectively. It is straightforward to show

from Table 3.2 that an the states can be eKpressed as a Iinear function of~ and ~ as shown

in Table 3.4 (the reader is reminded that an anaIogous result applies to the exergy states).

Since an the sta'..: variables must be nonnegative, the equations shown in Table 3.2 impose

the foUowing l"ecessa'Y and suflicient C{'nditions on the free variables ~ and ~ ,

•e. ~ 0

el Q Te7 +-s-+-

TJBB TJBB 1'JM

(3.21)

(3.22)

(3.23)

•

By plotting inequa1ities 3.21 through 3.23 in the ~ - ~ space, it is possible to ~snalizethe

region offeasible states in the sense that all are nonnegative and they satisfy a:I the system

equalities. See Figure 3.3. it can be noted that this region is bounded below by the ~ - Cr

axes and above by two Iines. The horizontal one simply represents the fàct that direct oil

heating cannot exceed the total space-heating end-use, Q. The inclined line represents the

fiIct that the output ofthe thermal power plant cannot be greater than the e1ectrical needs or

equivalently that the e1ectric generation must be nonnegative. It is useful to physica1ly

intertlret some ofthe vertices in this region. The point (0, Q), for example, implies that an of

_. - . space heating needs are met by direct oil heating and that there is no thermal power plant.


•

(o.Q)~=

(0.0)

Figure 3.3 Feasible region.

• Q)

•

The point (Q/11œ +T/1'JM, 0) corresponds to a system with no direct oil heating (orny e1ectric

baseboard heating) and ail the e1ectric needs supplied by thermal power plants.

In a more gen,;rai system, the region offeasible states becomes ofa higher dimension and

cannot be plotted but the principle is the same.

Now, since the design objective may be to maximize either the FlfSt or Second Principle

system efliciencieswithin the limits offeasibi1ity shown above, it is nece:;sary to express 3.17

and 3.18 in terms ofthe free variables~ and e,. This gives,


and

40

(3.24)

(3.25)

•

•

It can he seen that maximizing Tl is equivalent to mjnjmjzir ~ the denominator of(3.24). Ifwe

plot the locus ofconstant Tl in the l:t - ~ space, this will he a straight line with a negat!-Ie

s10pe. In Figure 3.4 three such loci are shown, 1')",;" , 1'J.l. and "l'lm.. , corresponding respectively

to the minimum, intennediate and maximum values ofthe FII'St Principle system efliciency

within the feaslble region. This figure clearly shows that to maximize Tl, one must operate at

(0,0), that is at the point where there is no direct oil heating and where there is no thermal

power plant generation, thus proving the statement made in equation 3.19. A simiIar argument

cao he made for lle Second Principle efliciency where the locus ofconstant E is represented

in Figure 3.4 by a straight line with a positive s1ope. Two such loci are shown, namely, E",;"

and e-.It is interesling to note that the maxinmm Second Principle system efliciency occurs

at (O,Q), that is, at a design with no thermal power plant and al1 space heating requirements

are met by direct heating. In addition, Figure 3.4 shows that the minimum exergy efliciency

design corresponds to the minimum energy efliciency design, both occurring at (Q/Tbm

+T/TlM' 0), that is, a design with no direct heating (100".10 e1ectric baseboard) and al1 the

e1ectric needs met by therma1 powerplants. This rigorously confirms the results stated earlier

in this ch3pter.

It is aIso worthwhiIe to note that for an intennediate rU'St Principle efliciency, 1'J.l" given by

•

•


Figure 3.4 First and Second Principle efficiencies oprirni7Jltion aspects.

41

the straight line locus shown in Figure 3.4, there exist an infinite number ofpossible solutions

an with the same F1Ist Principle efficiency b1.:t with different Second Principle efficiencies

which vary from a maximum at point a 10 a minimum at point b. This confirms the statement

made earlier that for a constant " there can exist numerous designs ofvarying E and vice-

versa.

FmalIy, consider an optirni7Jltion objective wbich rninirnizes a combination ofE and " such

as" + E or some other linear combination. It is c1ear that the locus ofan possible solutions

• that satis1Y thismixed objective will again begiven by a straight line but with a different s10pe


to those that bave as objective to maximize Tl or € alone. For example, the point (T/TlM , Q)

in Figure 3.4 is the optimum solution for an objective function f given by,

(3.26)

•

•

where w\ and W2 are positive weighting factors. Note also that fmay bave additional terms

re!ated to cost and emissions.

3.6 Computer Mode!

In order tû be able to f:2~ out the above-mentioned stu:lies, it was necessary to deve!op a

specialized so(..:~ tool [Oliveira & GaIiana, 1995a]. This tool, named EXAM (EXergy

Analysis Model), provides the userwith a set ofbasic constituent parts (resources, conversion

devices, end-uses) and a means to grapbically inter..onnect them to form an arbitrary

netwoIk. EXAM pennits the user to change the default values, to add new attributes and to

modifY the relationsbips among attrîbutes. To acbieve tiIis generality and flexibility, an object

oriented modelling approach was chosen using the generic environment G2, Version 3.0

[Gensym, 1992].


This ch2.pter bas presented a general mode! for the planning of e!eetric energy systems

including euergetic and exergetic considenmons. 'Ibrough an ü1ustrative example, this chapter

presents a grapbical interpret&tion ofthe main aspects ofenergetic and exergetic optimization.

•

•

•

Applications of Exergy Analysis in Electric Energy System Planning

Chapter4.

Applications ofExergy Analysis in

Electric Energy System Planning

4.1 Introduction

In this cbapter, severa! applications ofthe Second Principle in e1ectric energy system planning

are presented, name1y:

(i) The ana1ysis of the main e1ectric energy system end-uses: (a) space heating. (b)

cooking, (c) water heating. (d) traction, (e) Iighting. This ana1ysis is performed for

different system configurations including the following natural resources options:

hydraulic potenti:!1, Duclear energy, petroleum, coal and natural gas. The limiting

leve1s ofFPT and SPT efliciencies are calcnlated for each end-use under the best

possible system configurations;

43

• Applications of Exergy Analysis in Electric Energy System Planning 44

R-by - IClOlIrCC8 bydroR·th - forri! fuel

(pctrolcmn. uatural su,coa1) or .."cloar OIlo:gy

by - bydro polClltialth- thormalRe - rcfiJlcrypp - power p1alltTD - Innsmission Jm.c and

dirtrib"tio.. systemTP - tr8Illponatio.. ryrtemAIt - OIld-".e dcvicc altcmativcE""-".o i

Figure 4.1 Space heating modei.

•

(n) The impact ofperfoI1IlllLce improvement (PI) measures at the residential sector of

electric power systems is invesrigatetl at diffelent Ieveis, namely, the e1ectric appliance

being improved, the customer, the electric and gas/cil utilities and the overa11 natnra1

resources. Snch PI measnres inclnde the introdnction of more efficient e1ectrical

appliances, water-heaters or Iight bnlbs. Special attention is devoted to the influence

ofheat-gains due te cross-ejfects on beating and cooling loads. The impact ofsevera)

• PI u:.easures is examjned from the points ofview ofthe FII'St and Second Principles

• Applications of Exergy Analysis in Electric Energy System Planning

Table 4.1 End-uses, end-uses devices and natural resources considc:red.

4S

•

End-uses End-use Deviee Altcmative Natural Numbcc ofPossibleRcsourccs Configurations

Spacc hcating fumacc

Bascboard clcdric hcatcr Hydro cncrgy1. Spacc Hcating 18Hcat-pump air-to-air

Hcat-pump ground-to-airNuclcar cncrgy --

2. CookingDirect cooking stave

8Elcdric cooking

Pclrolcum

3. Watt:r hcatingDirect watcr hcating fumacc

8Elcdric watcr hcating

Incfticicnt motorNaturalgas

4. Traction 10Efficient motor

IncfIicicnt Iighting CoalS.Lighting

Efficient~10

of Thennodynamics for various PI measures, generation types and mix and space

heating alternatives.

(ùi) The energetic and exergetic impact of electric vehicles (EV) on Canada's power

systems is investigated. Different scenarios are eva1uated to simulate the incrcased

e1ectric demand due to the adoption of EV technology. These scenarios include

variations on the system load fàctor and changes in the e1ectric load through the

adoption ofmore energetical1y and exergetically efficient space heating alternatives.

The amount ofpetroleum that would he displaced ifEV were adopted as well as the

demand to build new power generation units are eva1uated. It is shown that there is

no need to build new e1ectric energy generation facilities for most ofthe Canad;an

• provinces ifa fraction ofthe space heating loads were converted to direct oil/gas

• Applications of Exergy Analysis in Eiectric Energy System Planning 46

space heating fumaces or to more efficient space heating options.

4.2 Limiting Levels of FPT and 8PT Efficiencies

This section is dedieated to the analysis ofthe limiting leve1s ofthe FPT and SPT efficiencies

for live end-uses: space heating, cooking, water heating, traction and Iighting under different

Table 4.2 Main system configurations.

Or cocffiCient-of-perfOlDlllDl:C

E 1).

End·use Code System coafiguration% %

SI Ground-to-aïr hcat-pump with hydroelcdricity 5.4 ID.7S2 Ground-to-aïr hcat-pump with natural gas 5.5 81.1S3 Grouod-uHIir bcat-pump with coal, ail or nuc1ear enc:rgy 5.4 80.0

1. Spacc 54 Air-to-aïr hcat.pump lIIId hydroelcdricity 4.2 148.6hcating S5 Spacc hcating fumacc using fossil fuel 3.9 57.2

S6 Air-to-aïr hcat-pump with fossil fuel orDuel.:cncrgy 3.6 53.3S7 Bascboard e1cdric heatcrs lIIId hydroelcdricity 2.5 87.4S8 Bascboard e1cdric heatcrs lIIId thcnnoclcdricity 2.1 31.5

CI Direct cooking range with fossil fuel 10.1 33.72.Cooking C2 Elcdric cooking with hydroelcdricity 5.6 44.6

C3 Elcdric cooking lIIId thcrmoelcdricity 4.8 16.0

3. Waœr WI DirectWlIlCr beating fumacc with fossil fuel 8.2 40.8

hcating W2 Elcdric WlIlCr hcating with hydroelcdricity 6.3 75.2W3 Elcdric WlIlCr beating lIIId thcrmoelcdricity 5.4 27.0

Tl Efficient motorwith hydroelcdricity 73.6 69.9

4. Traction T2 Efficient motorwith thcrmoelcdricity 63.0 25.1TI Inefficient motorwith hydroelcdricity 55.2 52.4T4 Inefficient motorwith thcrmoelcdricity 47.0 18.8

LI Efficient lisbtingwith hydroelcdricity 2.8 17.5

5. Ughting L2 Efficient Iightingwith thc:rmoelcdricity 2.4 6.3L3 Inefficient Iighling withhydroelcdricity 0.3 5.2L4 Inefficient Iighting with thcrmoelcdricity 0.2 1.9. .•

•

• Applications of Exergy Analysis in Eleetric Energy System Planning

Table 4.3 Main system configurations in decreasing order ofefliciency.

47

•

•

End-useSystem configuration in decreasing order ofefficiency

Second Principle First Principle

SI SIS2 S4S3 S7

1. Space bealing S4 S2SS S3S6 S6S7 SSS8 S8

Cl C22. Cooking C2 Cl

C3 C3

WI W23. Water bealing W2 WI

W3 W3

Tl Tl

4. Traction 1'2 T3T3 1'2T4 T4

LI LI

S. Ligbting L2 L2L3 L3L4 L4

system configurations. FlVe naturaI resources were tested: hydro, nuclear petroleum, naturaI

gas and coa!. Different tests were done to find out the limiting levels ofthe FPT and SPT

efficiencies of eacb end-use including the consideration of all possible combinations of

refineries, power-plants, transportation, transmission and distribution systems and end-uses.

See Figure 4.1.

Table 4.1 presents a Iist ofend-uses, end-use devices and naturaI resources considered in the


f --.----- ••• ------- -.- ••••••• --- •• - ••• --- •• -- •

•. . . . .6- -: :- - : .. -- ~ (]I) :. • Œtl . , .

Figure 4.2 Second, E, versus First, 1'), Principle efliciencies for the end-use space heating.

'-(S3 y.: : -- : -- :. , . .

5 " .

~~ . . . . .• • • • • •

4 - ........•. :.•• {~} - •. :•.•••.••.••: • - GD' : :il! : : : :

CE), .. H.~ (~'IH HH~I~1HH... 'H .. H.H. ,[~~~ )

2+---~--r------r------r------r--===="1

o 50 100 150 200 :25C~.in(%)•

calculation ofthe limiting leveIs ofthe FPT and SPT efliciencies. Similarly, for each end-use,

the nwnber ofpossible system configurations is also shown. Note that, for the space heating

end-use, four devices were considered, white, for each ofthe remaining end-uses, only two

aItematives were evaluated. As seen in Table 4.1, for the space heating end-use, the number

ofpossible system configurations is 18. This includes tbree possible space heating fùmaces

(gas, oil or gas from coal) and 15 el~c space heating configurations (tbree electric

alternatives tintes five natural resources).

•

For each of the possible configurations, the First and Second Principle efliciencies were

calculated. Table 4.2 shows the main types of system configurations and their F11'St and

Second Principle efliciencies. Table 4.3 summarizes, in decreasing order ofSecond and F11'St

Principle ofThennodynamics efliciencies, the typical configurations listed in Table 4.2. It is

expected tL..t realistic designs would have efliciencies 1ying inside the rr..nge defined by these


11 •••••••••• - - - ••••• - •• - - •••••••• - - - • - - • • • • • • - • • • • • -

tD • - - -. _ ••: _ •••• - - -:- • - - - •• - ~ - • - •• -@ : -.. -:• ........' • - - - - - - • 'e • • • • • • • : _ _ _ • • • • .'. _ _ _ • • • • 'p • • • • • • • pO-.j.. - ' '. -----.-, -'--.-.--.'. -.. - '!. . . , . . .

.!: • • , 1 • •

.; 7 •••••• - .' • - - - - •• - Op ••••• _ • J •• _ • _ ••• ' •••• _ ••• '•• _ ••••••'. . . . . .. . . , . .1· c , .......•........: : .. 5:)~· ~-- -> --:-- .... (SC;::~:l» --~ -.. ~~ -.~4 1 1 1 1 1.. •• ••

•Figure 4.3 Second, E, versus First, 1'), Principle efficiencies for the end-use cooking.

extreme limits. Analysing Tables 4.2 and 4.3, it is noticed that,

(i) There eKists a wide range ofenergetic and exergetic efficiencies for the set ofend-use

devices studied. The FPT efliciency (or coeflicient-ofperformance) ranges from 1.9"10

(lA) to 223.7"10 (SI) while the SPT ranges from 0.2% (lA) to 73.6% (TI);

(ü) The end-use traction bas the highest SPT efficiency (TI). Even the minimum e for

traction (T4) is higher tban the e for an other combinations ofend-uses and natural

(üi) Note that the heat-re\ated end-uses and lighting haVI:: an e- always less tban or equai

to 10.1%, as opposed to traction that reaches an eof73.6%;

(IV) For heat related end-uses, the maximum efficiency as measured by the Second

Principle ofThermodynamics occurs for the following configurations:

•(a) Space heating: ground-to-air heat-pump and hydre electricity (SI): Ifthe

heat-pump alternatives are not considered, then the maximum SPT occurs for

Sj!3CC heating fumace (SS). Note that even the air-to-air heat-pump with fossil


B5 •.••..•••••••••••.•••••••••••••••••.•••••••••••••

, . . . . ,. ..~. . . .B' ....•••.: ..•••... :.•~ ••• ; •••.•.••: •.••••. -;••••••.. :

7.5 - _. - ..• - -, . - . - - . - - ,- ....•.. :- - - - .••• -.•.••.•• '.' •• - - - . - .

7' _ ••••.•••••••••••••

. .8.5 ••••••••; •••••••• :•••••••• ~ ••••••••: •••••••• :••••• JW2 )

•

807D8050q.In~)

40

8 .•..•. Ci1J ~ : ~ ; :. . . . Ler;eDd J:'5.5 •••• ,.~ •.•••••• :•••••••• : ••••••• ~ •••••• SccTablc4.2 ::. . . .

s-t-~-~~-~,-~,~~,20• Figure 4.4 Second, e, versus First, 1'\, Principle efficiencies for the end-use water heating.

fuel or nuclear energy (S6) is Jess elI:ergeticel\y efficient tban the space heating

furnace (S5);

(b) Cooking: direct cooking furnace (Cl);

(c) Water heating: direct water heating with fossil fuel, (Wl);

(v) For heat related end-uses, the maximum efficiency as measured by the FIISt Principle

heat related end-uses, the maximum efliciency as measured by the FIISt Principle of

Thermodynamics occurs for the following configurations:

•(a) spaœ heating: ground-to-air heat-pump and hydro electricity (SI), followed

by air-to-air heat-pump and hydroeIectric generatiOD (84);


75] ~ : : ~ : Ii

70 •••••••• :••••••••• :. - •••••••: •••••••••: •••••••• ; ••••• Œ)· . . . . .

65- ..•..•.• :•.•..•... :--- :......•..: ; .

· " . . , ,....... ':' .GD' .':' ':' : : :1 • • • • ,....................................................... ,

. . . :GD.50· ••••••••••••••••• ',' ••••••• '.' ••••••• ',' ••••••• ; •••••••.

Figure 4.5 Second, e, versus First, 'l'J, Principle efficiencies for the end-use traction.

,:45 ·····cir·······:·········:········:········ . . .

•40

'0 20 30 40Il.ln(")

50

•

(b) Cooking: e1ectric coomg with hydroe1ectricity (S2);

(c) Water-heating: e1ectric water heating with hydroe1ectricity (W2);

(vi) The worst FPT and SPI' efliciencies coincide for the set ofconfigurations studied. In

an ofthe worst efficiency cases the energy is supplied by thermoe1ectric generation.

(vii) Comparing columns two and three ofTable 4.3, note that, with the exception ofthe

lighting end-use, an other end-uses have a different order ofdecreasing SPT and FPT

efficiencies;

(viii) Final1y, it is clear from the above discussion that, in general, for a given system

configuration, it is not possible to maximize both the FU'St and th~ Second Principle

efficiencies simu1taneously.

The question that presents itselfnow is how to compare energy system alternatives from the


3- . - - - - . - - - - - - - - - - - - - - - - - - - - -

. . '.Œ):

25- "-'-'---"'~"lifJ-"":"""""-'-:"""""--':2 • - ••• - •••••• , •••••••••••• ~ •••••••••• - • -,- - - ••••• - ••••.

. , .- - ~ ~ - . -,- - - . - - - - . - .

, - - . - - . ~ - : : - .

Figure 4.6 Seco:lll, c;, versus F1I'St, l'J, Principle efficiencies for the end-use Iighting.

5

•o.s-

oo

. . . . . . . . . . . . , - .. - . - .' - '- - _.,------...,-

• Œ) ~ @), : Scc~~2 jro ~ ~

q.1n (%)

•

combined points ofview ofenergy and exergy (excluding cost for the moment). Figures 4.2

to 4.6 show, for each end-use, (space heating, coolàng, water heating, traction and Iighting)

in graphical fc:m, the information presented in Tables 4.2, by plotting the FPT efficiency

against ~j,~ SPT efficiency for each configuration listed. Note that, for these five figures, the

system Cln11lguration shown corresponds to the ones Iisted in Table 4.2. Cost will, ofcourse,

play a role in the fiIll..\ analysis lII:d is further discussed in Chapter 5.

One can argue that cll the proposee! alteri1lltives are extreme cases of only one type of

generation and end-use and arc unlikely to be realized. Nevertheless, these cases provide

benchmar\c Iimits which cau neverheexceeded by any alternative. For example, for the space

heating end-use, SI (hydroeIectric poV':c.- with ground-to-air heat-pump) is the limiting

alternative because of its highest Fust 3Ild Second Principle performance. The worst

alternative for tŒs end-use from both Pr'.nciples is S8 (thermoelectric generation with


•

•

baseboard electric heaters). For space heating, saturation through direct gas or oi. heating,

is an alternative that is more like1y to be approached since it implies changes in the end-use

heating systems and not in the generation mix ofthe utility.

4.3 Demand Side Management Performance Improvement

Demand Side Management (DSM) is recognized by e1ectric utilities and society as an

attractive alternative to system expansion and ~.s a resource to be planned [Ra!>l, 1991). In

1990, Latorre et al studied the application of DSM techniques in the industrial sector

concluding that the cost ofelectric energy saved by DSM was estimated to be between 12 and

21 US$/MWh whereas the marginal ('.ost of expansion was estimated to be around 62

US$IMWh. Similarly, a study in British Columbia [Henriques, 1992] indieates that the cost

of a DSM program is Can$16/MWh compared to Can$50/MWh to generate equivalent

energy with new power plants. One important DSM measure, known as Performance

Improvement (PI) [Talukdar & GeDings, 1987], consists of incentive programs to encourage

the rep1acement of electrical equipment 1»' more efficient substitutes. Examples of PI

measures are: (i) Rep1acement of incandescent by fluorescent compact lighting, (ü)

installation ofmore efficient water heaters, (ili) switching to more efficient motoTS.

DSM Performance Improvement measures cannot be eva1uated by only cCinsidering the

energy savings at the level of the equipment being rep1aced, since these Sllvings spread

throUghOl.lt the entire energy system. Thus, implementing a PI measure for one type ofenergy

conversion device will also influence various other level.s ofthe energy systema11 the way

~ack to the natural resources level. Similarly, a PI measure will affect the consumption of

energyby ether load.s at the same level Decallse ofthe phenomenon known as eross-effects.

Atypical example ofeross-effects is the impact ofimproving the performance ofany indcor


•

•

energy conversion device on the space heating and cooling requirements ofa dwelling. In a

study conducted by a Cnnadian utility [Moreau & Stricker, 1994], it is demonstrated, for a

given type ofhouse in Montreal, that a more efficient water heater economizing 438 kWh /yr

resu1ts in ollly 42"10 ofthese savings being rea1ized at the dwelling or customer leveI. This is

50 since, as a result ofthe increased water heater efficiency, less nc:ll is released indoors as

heat loss and therefore the space heating requirements increase by 291 kWh/yr during the

heating season. Similarly, the air-conditiofÜng requirements decrease by 38 kWh/yr during

the cooling season. Outside the cooling or heating seasons, the energy saved does not

significantIy etreet ether heat-reIated loads. Note that ifone propagates these net savings at

the dwelling back to the natural resources, the accumulated benefits can be considerably

more substantiaI depending on the generation mix.

The purpose ofthis example is to report on the impact ofDSM performance improvement

measures from both the energetic and exergetic points ofview and with emphasis on cross

etlèets. One important reason for developing broad perspectives in anaIysing DSM strategies

is to provide planners with more systematic means to evaluate and prioritize different PI

alternatives.

4.3.1 :Basic energy conversion model element

To understand how an energy model is constructed, first consider Figure 4.7 showing an

arbitrary basic energy conversion element. Let Et and E.z represent the input and output

yearly energy values of tI:~ element. SimiIarly Xl and X 2 represent the corresponding

exergetic values. Let TJ and e represent respectively the energetic and exergetic efficiencies.

Then, the following relations hold,

(4.1)

• Applications of Exergy Analysis in Eleetric Energy System Planning

1E, ~ E2 ...,

En~ Conversion,.

~anal!

X,.... tl. E ~~ ,

,t ,ifx =Excrgy x ="y~cbt dcslnJclion ... ~pated

55

•1 -----1

Figure 4.7 Energy conversion elemen~

(4.2)

Since energy is conserved,

(4.3)

the energy dissipated in the form ofheat to the environment is,

(4.4)

•On the other band, exergy is not conserved in any conversion process, 50 that,

• Applications of Exergy Analysis in Electric Energy System Planning S6

(4.5)

where x.- is the exergetic content ofthe energy dissipated as heat. The irreversible exergy

destruction, X-, that a1ways takes place is given by,

(4.6)

•In addition, for any process it is possible to estimate what fraction of the input (al) and

outpl1t lexJ energies Cêdl be converted to available work (exergy). Then,

(4.7)

Because ofequations (4.1), (4.2) and (4.7), it is necessa'Y that the energetic and exergetic

efliciencies satisfy the ratio,

(4.8)

•Table 2.1 in Chapter 2 shows, for a set ofenergy conversion devices, the as.<;umed values of

the efficiencies according10 the FIISt and Second Principles ofThermodynamics ('1'), E) as weil

as the fraction ofthe input (am) and outPut (a....) energy that can be converted to work. In

this Table, the a's are estimated ~snming the most efficient available technology to convert

a given form ofenergy into available work.


•

For example, for a 1 kW basc:board space heater, where the input is electricity and the

output is heat al 20 degrees C, Ctl is approxirnately 95% (based on the highest efficiencj of

electric motors) while ~ is 6.8% (based on the ideal Carnot cycle efficiency with

temperantres of20 and 0 degrees C). Since an electric baseboard heater is 100"10 energetically

efficient, its exergetic efficiency (e) is 100* 6.8/95 = 7.2%. Therefore, whereas 100% of

the input energy is converted to a usefu1 output in the form ofheat, 92.8% ofthe input exergy

is destroyed by this process.

4.3.2 Mode! with cross-effects

Figure 4.8 shows another example ofa su:Jsystem with a combination ofbasic elements

including cross-effects. It consists of air-conditioning (AC), light (LT) and space heating

(SR). The end-uses are cooling (C), illumination (1) and heating (H). In this example, ooly

the energy quantities are disp1ayed. A simiIar set ofvariables and relations apply to the exergy

balance. The input/output relation ofeach energy conversion element in Figure 4.8 yields,

(4.9)

(4.10)

(4.11)

•cross-effects complieate the pieture as seen in Figure 4.8 since seme fraction (~I) of the

lighting device (LT) losses, (1-1lJ E:" as weil as another fraction (en) ofthe illumination

end-use ~atributes to the heating requirement. A similar but opposite effect occurs with

respeci: to the cooling needs. These cross-effects are modelled by,


• Figure 4.8 Typical subsystem containing cross-effects.

1 - E- 4

c

(4.12)

(4.13)

(4.14)

•

where E:z is the output ofthe Air Conditioner (AC) and E, is the net cross-e1fect on the AC

due to the heating effects ofthe Iighting process. Clearly, for a given cooling end-use, C, the

impact ofthe cross-effeet, E" is to force an increase in the output energy ofthe AC,~.

Alternative1y, the impact ofthe Iighting cross-effeet, Eu. is to decrease the output .:>fthe

SpaceHeater, ~, in order to meet the bearing end-use, H. The cros.<.-t...fect energi~, E, and


El2 , each have two components,

59

(4.15)

(4.16)

the component~ is a fraction (cu) ofthe Iighting device losses during the cooling season,

while ElO is a fraction (c:n) ofthe Iighting device losses during the heating season.

•E, = Cil (1 - TIL ) ~ (4.17)

(4.18)

Simi1arly, Es and ~l respectively represent fractions ofthe summer and winter Iighting end

use which are converted to heat and affect the cooling and space heating end-uses. These

fractions Cat are estimated in the model from utility and government statistics [Moreau and

Stricker, 1994]. It should be noted that Er +~o must be less than the total yearly Iighting

load losses, (1- "ù.) E:J, due to the fàct that sorne losses occur outside the cooling or heating

seasons. Simi\arly, Es+~l must be less than the illumination, 1, due to two facts: One is that

sorne ofthe Iight escapes through windows without being converted to heat indoors. The

second, as before, is that the heat produced by Iight bas no effect on heat-related loads

outside ofthe cooling or heating seasons.


•

•

4.3.3 System impact of DSM PeJformance Improvement strategies

description ofCase-studies

In this section, a representative set ofcase-studies is discussed including:

(1) The impact ofperformance improvement DSM strategies at various system levels,

namely a;,pliance, customer, utilities and overa!l naturaI resources.

(2) The impact ofthese PI measures in terms ofenergy and exergy savings at the various

system levels.

(3) The impact ofCTOss-effects on heat-re\at~ loads.

(4) The impact ofPI measures under different system configurations. These consist of

various combinations ofnatural resources, power plants, refineries and space-heating

devices.

(5) The effect ofdifferent climates and dwel1ing insulation levels.

Table 4.4 Energy system configurations considered.

Type Type ofGeneration Type ofSpace Heating

Cl Electric base-board

C2 Hydro-e1ectricity Heat-pump ground-to-air

C3 Direct oil\gas heating

C4 Electric base-board

CS Thermal-electricity Heat-pump ground to air

C6 Direct oil\gas heating


•

•

TAble 4.4 presents the savings assumed at the appliance level due to the implementation of

three different PI alternatives, namely, the introduction at the residential level of more

efficient lighting, e1ectric water heaters, and refrigerators. These energy data (assuming a

well-insulated dwelling in Montreal) [Moreau and Stricker, 1994] represent the predicted

yeariy savings for the appliance only, that is, without cotsidering cross-effects. The exergetic

savings shown in Table 4.4 are based on the assumption that 95% ofthe energy savings could

be converted into work through an efficient e1ectric motor. To evaluate the impact ofPI

measures at the various levels ofan energy system (appliance, customer, utilities and natura!

resources), six diffèrent energy system configurations were studied as descn1led in Table 4.5.

These system configurations were simulated and include two types ofe1ectric generation:

hydro and thermal, and three types ofspace heating devices: baseboard considered being

100% efficient, ground-to-air heat-pump with a coefficient ofperformance of300% and a

direct oil or sas heater with 81% efliciency. These configurations were selected l>ecause they

represent extIeme cases of generation and space-heating types. Other space heating

alternatives such as the more common air-to-air heat-pump lie in between the two e1ectric

space heating types shown in Table 4.5.

The Sl..JÏngs at the customer Ieve\ are definee: by the net equivalent kWh yearly savings from

Table 4.5 Energy and exergy savings at the appliance Ieve\.

Savings at the Appliance Leve)

Performance Improvement in equivalent kWb/yearMeasure

Energyt Exergy

PI-l ImprovedRefrigerator 353 335

PI-2 Efficient Eectric Water Heater 438 416

PI-3 Replacement ofIncandescent by 518 493Compact Fluorescent Light Bulbs

.


the heating and cooling devices including cross-effects.

62

•

•

Two types ofutiIities are considered in this thesis, namely, e1ectric and g3Sfoil. The savings

due to the introduction ofa PI measure are calculated for each utility at the input level.

Finally, the combined utility savings define the net naturaI resource savings.

4.3.4 Evaluation 'IfPI Measures

Tables 4.6, 4.7 as weil as the Tables BI to B4 shown in the Appendix, summarize the

simulation resuIts obtained for the cases defined in the previous section. The Tables contain

six rows, each corresponding to a system configuration as Iisted in Table 4.4. In addition, the

Table 4.6 Energetic savings at diffèrent system levels for PI 'Improved Refiigerator'.

Encrgy Savingsin cquivalent kWhlycarJc:ustomer

CoofigmalionNet

Appliancc Cooling Sp8l:C Dwc1Iing Electtic GaslOii RcsourceHeating Uti1ity Uti1ity Savings

Cl 353 27 -216 164 192 0 192

C2 353 27 -72 30B 360 0 360

C3 353 27 -266 114 444 -304 140

C4 353 27 -216 164 561 0 561

CS 353 27 -72 30B 1051 0 1051

C6 353 27 -266 114 1296 -304 992


•

•

columns of each Table indicate the savings at different system levels. Fmally, for each

Performance Improvement measure listed in Table 4.4, two tables are shown, one for energy

and another for exergy savings.

The numerous results shown in these six Tables are analysed according to the foUowing

points:

(A) Impact ofcross-effects;

(B) Comparison ofsavings at different system levels and configurations;

(C) Comparison ofenergetic and exergetic savings;

(ù) Comparison ofdifferent PI measures;

(E) "fhe effect ofdiiferent climates and dwelling insulation levels.

As discussed in above, because ofthe influence ofcross-effects on heating and cooling loads,

the net savings at the dwelling level di1fer significantly from the savings at the appliance level.

Table 4,7 Exergetic savings at different system levels for PI 'Improved Refrigerator'.

ExclBY Savinssin equivoJc:nt kWhlyoarl=-

ConfigurationGasIOiI Net

Appliancc Cooling Spacc DweUing EIcclric UtiJity ReoowccH<aling UtiJity Savinss

Cl 335 26 -205 156 183 0 183

C2 335 26 -68 293 342 0 342

C3 335 26 -98 263 422 -113 309

C4 335 26 -205 156 208 0 208

C5 335 26 -68 293 389 0 389

C6 335 26 -98 263 479 -113 366


•

•

In order to discuss this point, consider Table 4.6 showing the energy savings for the PI

measure 'irnproved Refiigerator'. The following observations cao be made:

(i) Because ofcross-effects, the net energetic savings at the customer (dwelling) level are

considerably less than at the appliance level. The net eustomer energetic savings f::nge

from 32% to 87% of those at the appliance leve1 depending on the system

configuration.

(ü) Column 2 indicates the assumed savings at the appliance leve1. Column 3 shows the

savings in the cooling load during the summer months, while column 4 indieates

negative savings in the heating system due to the faet that the improved refiigerator

releases less residual heat during the heating season. These savings differ according

to the efficiency ofthe space heating system. Thus, the least efficient space heater

(direct heating) must work harder to make up for the missing residual heat resuIting

in a reduced net savings at the dwelling 1eve1. Column 5 shows the net savings at the

dwe1ling whieb are the sum ofcolumns 2,3 and 4. The worst impaet ofcross-effects

occurs for configuration C3 (hydroe1ectric generation combined with direct oil/gas

heating) where ofthe 353 kWh/year saved at the appliance leve1 only 114 kWh!year

or 32"10 are saved at the dweIIiIlg 1eve1. The least damaging impact ofcross-effects at

the dwelling 1eve1 takes place for configurations C2 and CS, both of~hich use the

very efficient ground-to-air heat-pump.

4.3.5 ComparisoD of savings at ditTerent system leve1s

The net savings propagate beyond the dwe1Iing leve1 toward the utilities and natural resources

by diffdeut amocnts depending on the system configuration and the individuaI efficiencies of

each energy conversion process (See Table 2.1 in Chapter 2). Continuing with Table 4.6, the


following observations are made:

65

•

•

(i) Columns 6 and 7 show respectively the savings at the electric utility and gas or oil

utilities. Column 8 represents the total natural resources saved which is the sum of

the savings at a1l utilities;

(ri) The savings at the electric utility are always larger than at th~ dwelling due to

transmission and generation losses;

(ili) In the configurations where there is direct space heating, the savings at the electric

utility are even higher since the increased demand on space heating due to cross

effects will affect only the gas/oil utility where the savings are negative;

(iv) The maximum savings at the electric utility level occur for C6 (thennoelectric

generation and direct heating) mainly due to the low efficiency ofthe thennal power

plant (35%);

(v) At the resource level (column 8), the savings are highest for configurations CS and

C6, confirming that the greatest impact ofa PI measure is felt in the least efficient

system.

4.3.6 Comparison ofenergetic and exergetic savings

The corresponding ex:ergetic savings ofthe PI 'Improved Refiigerator' are shown in Table

4.7 The fullowing observations are made:

(i) Because ofcross-effects, the net ex:ergetic savings, at the dwelling level, lire aIso

lower than at the appliance level.

(ri) When two dilfaent sources ofenergy are used in a given configuration, the exergetic

Applications of Exergy Analysis in Electric Energy System Planning 66

•

•

savings at the natura! resource and dwel1ing levels are comparativel)' higher than the

energy savings. Thus for C3 (hydroelectric generation plus direct heating), as an

example, the exergy savings at the natura! resource level are 93% of those at the

appliance level while the comparable energy savings are only 40%. This is e.xplained

by the faet that the exergy content in oil or gas is lower (37%) than in e1eetricity

(95%). Thus, for every extra equivalent kWh demand in oiVgas only 0.37 kWh

equivalent ofextra exergy will be required. These differences in behaviour highlight

the importance ofexergetic analysis in systems with multiple types ofenergy sources

and conversion processes.

(ùi) Comparing Cl (hydroe1ectric generation plus baseboard space heating) with C3

(hydroelectric generation and direct space heating), at the natura! resource level, the

energy savings ofCl are 31010 higher than for O. Alternatively, the corresponding

exergy savings for Cl are 69% lower than for C3 for the same reasons as in (ü).

(iv) Although from the point ofview ofenergy, the savings at the resource level vary over

a range of approximate1y one to seven for the six configurations studied, the

corresponding eltergy savings only vary over a range ofone to !Wo. Thus, the impact

ofthis PI measure from the point ofview ofexergy savings is not as striking as from

the energy savings perspective.

4.3.7 Comparison ofdifferent performance improvement measures

Tables B2, B3, B4 and B5 in the Appendix show the corresponding energetic and eltergetic

savings for the rernaining !WO PI measures: 'Efficient Electric Water Heater' and

'Replacement ofIncandescent by Fluorescent Light Bulbs'.


Table 4.8 Use ofthe energy in an typical ga;:..,line powered ICEV.

67

•

•

Fraction ofthe energy contentin the gasoline %

Energy Conversion StepCrouse & Anglin DeCicco & Ross Québec

(1987) (1994) (1992)

1. Lest in cooling water air and oil 3560

2. Lest in the exhaust gas 35

3. Lest in the engine fric: :')n 580.021

4. Lest in power train 10

5. Lest in the brakes - 4.7

6. Left to propel the vehicle 15.0 14.3 20.0

7. Total 100.0 100.0 100.0

The foUowing points are made about PI measures in general:

(i) The absolute savings at the appliance Ievel difi'er over the PI'S, but the relative effects

at the various system levels are approximately in the same proportion. The observed

percent difFerences among the prs arise mainly due to variations in the cross-effects.

For example, considering configuration C6, the energy savings at the natura1 resource

Ievel as a percent ofthe appliance savings are respectively 2810/0, 274% and 280% for

the three PI measures;

(û) Other PI measures, not diSQIssed here, could result in much wider differences due to

variations in cross-elfects. For example, the use ofan efficient washing machine with

cold water bas a low cross-effect impact on the heating load;


4.3.8 The efTect of difTerent dimates and dwelling insulation leveJs

68

•

•

The effect ofthe climate on the energetic and exergetic savings for a given PI measure was

tested in the following Canaclian cities: Montreal, Vancouver, WlDlIÏpeg. Toronto, Halifax and

Fredericton. The PI measure 'Efficient E1ectric Water-heater' was simulated for these cities

fo~ both configurations Cl (hydroeJectric generation with eJectric baseboard space-heating)

and C4 (thermoeJectric generation with eJectric baseboard space-heating). The energetic and

exergetic savings varied between 87"/0 (W1DDÏpeg) and 135% (Vancouver) of the savings

achieved in Montreal. For the cities studied, it seems that the warmer the climate, the Jess

significant is the impact ofcross-effects.

Three types ofdwe1ling thermal characteristics were considered: Type A (poorly insulated),

type B (weil insulated) and type C (very weil insulated). The influence ofthe dwe1ling thermal

cbaracteristics were studied for the system configurations Cl and C4. The energetic and

exergetic savings varied between 95% (dwe1ling poorly insulated) to 112% ( dwe1ling very

well insnJated) ofthe savings in the dwe1ling type B (well insulated).

For the cases studied, the climate bas a stronger effect on both energy and exergy savings

tban the thermal characteristics ofthe dwe1ling

4.4 Energetic and Exergetic Impact ofElectric Vehicles in Canada

4.4.1 Introduction

The Canadian transportation sector consumed 26% ofthe totaI energy consumption in 1995.

Of this total, 82% accounts for the road transportation and the remaining 18% for air, water

Applications of Exergy Analysis in Electric Energy System Planning

Table 4.9 Electric vehicle characteristics.

69

•

•

Sub-compactSmall van Large van

EV perfonnance item car

1995 2010 1995 2010 1995 2010

1. Driving range (km) 160 320 160 320 130 240

2. Extra weight (kg) 560 266 812 457 809 397

3. Efficiency loss factor, Wf (%) 18.6 12.0 19.0 13.6 16.6 10.1(Due to extra weight in the EV)

4. Consumption ratio lCEVIEV, Cr 2.62 4.04 2.62 4.04 2.71 4.25

5. EV consumption ( kWnIIan) 0.35 0.20 0.48 0.30 0.62 0.38Source: [Wang & DcLuchi. 1992]

and rail transportation [Canada, 1994).

The recent and predicted improvements in eIectrical vehicles (EV) technology raises some

questions in the energy planning sector regarding primary energy consumption, petroleum

displacement, air emissions and system efficiency.

A more intensive use ofEV's is expeeted to reduce air emissions [Gellings, 1993]. The

principal emissions that contribute to urban air pollution are volatile organic compounds

(VOC) and nitrogen oxides (NOx), bath precursors ofozone and carbon monoxide. Canada

bas signed a series ofprotocols [Canada. 1992) to: (i) Reduce the VOC emissions by 30010

ofthe 19881eve1sby 1999; (ù) Reduce annuai emissions ofNOx from stationary sources by

100,000 tonnes per year below the year 2000 forecast leveI of970,OOO tonnes. Besides the

beneficial effects of decreasing the air emission leve1s, the adoption ofEV will certainly

dccrease the energy dependency leveI from energy sources outside the respective province

or planning region.


To perform the energetic and exergetic anaIysis ofthis scenario it is important to evaluate the

efficiencies ofthe processes in question. T1ùs is the subject of the ne.'I."! section.

4.4.2 Evaluation of dectric vehicle (EV) and intemal combustion

engine vehicle (lCEV) efficiencies.

Analysis ofthe energy conversion processes that take place in an internai combustion engine

vebicle (ICEV) shows that only a small fraction of the energy content in the fuel is aetually

used to prepel the car [Creuse & Anglin, 1987, DeCicco & Ross 1994, Québec 1992]. Table

4.8 shows the fraction ofthe energy content in the gasoline that is aetually used for different

energy conversion stages in the ICEV's. Qnly between around 14.3% and 20010 ofthe heat

content ofthe fuel is used to propel the car. These figures rep:-esent the efficiency assessed

by either First or Second Principle since it is considered here that the end-use road

transportation is 100% exergy (work). The dissipated energy, at least 80%, is used mostly

for: cooling, braking, fiiction and gases escaping through the exhaust system.

Table 4.10 Forecast fuel consumption (IanIl) and weight (kg) of ICEvt.

Model

Year Item Sub-compaet Small Vans Large VansCars

kmJ1 9.8 6.8 5.11995

kg 1248.5 1747.9 2111.1-c_

kmJ1 13.4 8.2 6.12010

kg 1066.9 1566.3 1974.9.

t ICEV = intemal combUSllon engmc vcbic1esSource: (Wang & DeLuchi, 1992]•


Table 4.11 First (1]) and Second (e) Principle efficiencies for ICEV and EV.

71

•

•

Sub-compact car and sma\I van

Type ofVehicle 1995 2010

n e n e

1. Internai Combustion 14.5 33.7 19.8 46.0Engine Vehicle ICEV

2. E1ectrica1 Vehicle EV 30.9 32.5 70.4 74.1

Wang and DeLuchi (1992) have conducted a study about the impact ofe1ectric vehicles on

the primary energy consumption and petroleum displacement. The ana\ysis was conducted for

difièient sizes ofvehic\es, subcompaet cars, small vans and large vans for the years 1995 and

2010. In that study, the authors compared the consumption per kilometre using the following

primary energy sources ofenergy: coal, crude oil, naturaI gas and biomass.

It was shawn that, between 1975 and 1990, the fuel consumption ofnew passenger cars had

improved from 5.6 to 9.8 km/\, resulting in an improvement rate ofapproximately 3.8% per

year during that period. The internai combustion engine vehicle (ICEV) is expected to further

improve its fuel consumption by 1.55% between 1990 and 2010 under a cost-effective

scenario, reaching 13.41an11 for a subcompact car. At the same time, the subcompact car

weight is expected 10 decrease from 124910 1067 kg. It is important to note at this time, that

severa! studies have demonstrated that alO"I. change in the vehic\e weight canses a 6%

change its performance [Unnewehr & Nasar, 1982; Bnssmann, 1990; Amann, 1990; Bleviss,

1988]. Table 4.9 shows the substantial forecast fuel consumption and weight for the internaI

combustion engine vehic\es.

Table 4.10 presents SOIJ1(; characteristics ofthe e1ectric vehic\es, inc\uding the driving range,


Table 4.12 Configurations considered for road transportation.

72

•

Code Natural resource Type ofvehic1e

A ICEVPetroleurn

B EV

C EVBiomass

D ICEV

1E NaturaiGas EV

F ICEVCoal

G EV

H Hydro Potential EV

the extra weight of the EV compare<! to the ICEV and the EV energy consumption in

(kWhJlan). Other cbaracteristics ofthe EV are shown in Table 4.9 as weil such as efficiency

1055 fàctor, Wc and the consumption ratio ICEVIEV, Cr

The FPT efliciency of the ICEV (Thav) considered in this study was 14.5 %, for 1995. The

FPT efliciency ofthe EV ('lEV) is given by,

'lEV = TJJCEY Cr (1 - W) (4.19)

whereCristheconsumptionratio ICEVIEV shown in Table 4.10. Wc is the efliciency 1055

fàctor due to extra weight ofthe EV and it is given by [Wang & DeLuchi, 1992]:

•(4.20)


•

•

where Cr is the consumption ratio ICEVIEV shown in Table 4.10. Wr is the efliciency 1055

factor due to extra weight ofthe EV and it is given by [Wang & DeLuchi, 1992]:

Table 4.11 presents, for a subcompact EV and ICEV car and a small van, the First and

Second Principl~ efficiencies for 1995 and 2010. The SPT efliciencies of the cars were

calculatOO estimating that the available work in the fossi! fuel source is 43% and in the

e1ectricity 95%. The usefuI work ofthe enC:-use road transportation was co~derOO to be the

same as the usefuI energy produced bythe car. AnalysingTable 4.10, it is notOO th:lt, in 1995,

the FPT efliciency for the lCEV was less than halfthat of the EV but the FPT and SPT

efficiencies were around 33%. For the year 2010, bath FPT lI!Id SPT efliciencies ofthe EV

are substantially larger than the equivalent for the lCEV.

4.4.3 Energy system with EV and ICEV

A rational use ofthe different sources ofenergy with respect to their exergetic content is

accomplished bythe appropriate matching ofthe energy source to the end-use required. For

this reason, it is important to evaluate the EV and lCEV efliciencies under different system

configurations. Wang and DeLucbi (1992) estimate the overall FPT efficiency ofseven energy

production processes, having as primaJy energy source petroleum, coat, naturaI gas and

biomass. They estimate the process efficiency from the naturaI resource to the service station

(lCEV case) or to the wall outlet (EV case). In this thesis, the configurations studiOO by

Wang and DeLucbi (1992) were extendOO to include hydroelectric resources. In addition, the

FPT and SPT efficiencies from the naturaI resources to the road transportation end-use were

calcu1atOO. Table 4.12 shows the eight configurations that were studied. Figure 4.9 shows

the energy transformation mode! considered for road transportation. In order to calculate the

exergetic efficiency ofeach configuration, the available work in each ofthe sources must be


.----~o{oGT__---4..

74

• CR - =de ror:ow:ryCT-cn:dc1nDsporlCF - crudc roliDayGT - gasolinc1nIIlspcxtFT - fùcI oillrllllsperlllÏOIlP 0 - J>O'M:r plaIIt petroIcumTI. - tnmsmissiœ bDC

•

YJgUre 4.9 Road transportation mode! for intemal combustion engine vehic1es and e!ectricalvehic1es.

estimated. In this thesis it is collSÏdered that the available work in petroleum, biomass, natural

gas, coal, hydro potential is43, 36, 43, 43, and 95% respectively. Table 4.13 and 4.14 specify

the FPT efliciency ofeach ofthe energy conversion steps collSÏdered, for the years 1995 and

2010, respectively.

Finally Table 4.15 summarizes the overa11 FPT and SPT eiiiciencies of each of the

configurations collSÏdered in Tables 4.13 and 4.14. Analysing Table 4.15, note that:

Regarding the year 1995:


•

•

Table 4.13 F1I'St Principle efficiency for eight configurations for road transportation in 1995.

1 EIT"ICieDcy.1n pemDt (1995) 1ConJï""llltion (A) Pc:trolcum-ICEV ConJi""..ation (B) Petrolcum-EV

CR - Crude Rccovcty 96.9 CR - Crude Rccovcty 96.9

CT - Crudc llllnapOrt 98.9 CT· Crudc llllnapOrt 98.9

CF· Crude Rcfincry 87.4 CF· Crode Rcfincry 95.2

GT • Gaaoline Transport 99.2 FT· Fuel Où Transport 993P_O, Power Plant Petrolcum 32.0

TL· Transmission Linos 92.0

Sc:rvicc Station 83.1 Wall Outlcr 26.7

lntcmal Combustion Engine Vchicle (ICEV) 14.5 E1ccrric Vchiclc (EV) 30.9

TJ p tCF.V 12.1 TJ p F.V 8.3

ConJiauration (C) BiOlllllSS-EV ConJiauration (E) Narura1 Gas-EVBP ·Biomass Production 92.7 GE· Gas Extraction and Gathcring 93.7

BT • Biomass Transport 99.2 GT • Gas Transport 963

BL· Biomass Liquefaction 60.0 P_G • Power PlantNatulll1 Gas 323LT • Syncrudc Transport 99.0 TL· Transmission Linos 92.0

P_B· Power Plant Biomass 32.5

TL· Transmission Linc 92.0

WalIOuUcr 163 WalIOuUct 26.8

Elccrric Vchiclc (EV) 30.9 E1ccrric Vchiclc (EV) 30.9

TJ B F.V S.O TJI'UV 8.3

ConJiRUllltion (F) CooI·1CEV ConJiauration (Q) CoaI-EVCM· Cool Mining 98.1 CM· Cool Mining 9S.l

T_1 • Cool Transport 993 T_2· Cool Transport 99.0

CL· Cool Liquefaction 60.0 P_C • Power Plant Cool 33.5

SR· Syncrudc refincry 87.4 TL· Transmission Lincs 92.0

ST· Syngasolinc Transport 99.2

Sc:rvicc Station 50.7 WalIOuUct 29.9

Intcmal Combustion Enginc Vchiclc (ICEV) 14.5 EIccrric Vchiclc (EV) 30.9

'1 B F.V 7.4 TJ C F.V 9.2

ConJiauration (D) Biomass-ICEV ConJiauration (HlH~EV

BP·Biomass Production 92.7 P_H· Hydra PowerPlant 95.0BT • BiomassTransport 99.2 TL· Transmission Iioc 94.0

BL ·Biomass Liquefaction 60.0

LR· Syncrudc Rcfincry 87.4

RT· Rcfincd Transport 99.2ScrviocStation 4S.2 WalIOuUct 87.4

lDtcmaI Combustion Enginc VchicIc (ICEV) 14.5 EIccrric VchicIc (EV) 30.9

11 R ,,...,, 7.0 11 v ""27.0


•

•

Table 4.14 First Principle efliciency for eight configurations for road transportation in 2010.

ElrlCÎene>',1n perœnl (2010)

Confi.uration (A) PctIDlcum-1CEV Confioullltion (S) PctIDlcum-EVCR - Crude Rccovcty 96.9 CR - CNde RccovCl)' 96.9

CT - Crudc llllnSpOrt 508.9 CT - Crudc llllnSpOrt 98.9

CF - CNde RcfinCl)' 87.4 CF - Crudc RefinCl)' 96.:!

GT· Gasoline Transport 99.2 FT - Fuel Cil Transport 99.3

P_0 - Power Plant PctIDlcum 39.0

TL - Transmis3ion Lines 94.0

Sctvicc Station 83.1 WallOudct 33.6

intemal Combustion Engine Vehicle (lCEV) 19.8 E1cctrie Vehicle (EV) 70.4

TI P leEV16.5 11 P F.V 23.6

Confilt\ltlllion (C) BiOllll.....EV Confi.Ullltion CE) N.tural Gas-EVBP ·BiomassPtoduction 92.7 GE - Gas Extraction and Gathcring 93.7

BT - Biomass Transport 99.2 Gr· Gas Transport 9S.3

BL - Biomass Liquefaction 80.0 P_G- Pnwer Plant N.tural Gas 43.0

LT - Syncrudc Transport 99.0 TL - Transmis3ion Lines 94.0

P_B - Power Plant Biomass 35.0

TL - Transmis3ion Line 94.0

WallOudct 14.5 WallOuUct 36.5

E1cctrie Vchicle (EV) 70.4 E1cctrie Vchicle (EV) 70.4

TI B F.V 10.2 11 N F.V25.7

Confiouration (F) Coa1-ICEV Confio=tion (G) Coa1·EVCM - Coa1 Mining 98.1 CM· Coa1 Mining 98.1

T_1 - Coa1 Transport 993 T_2 • Coa1 Transport 99.0

CL - Coa1 Liquefaction 70.0 P_C • Power PIanI Coal 39.0

SR· Syncrudc refincty 87.4 TL· Transmission Lines 94.0

ST· Syngasolinc Transport 99.2

Sctvicc Station 59.1 Wall 0u1Ict 35.6

intemal Combustion Engine Vchicle (lCEV) 19.8 E1cctrie Vchiclc (EV) 70.4

11 B EV IL7 TI c F.V25.1

Confio=tion (D) Biomaso-lCEV ConfiOWlltion IH)HWIOoEVBP·Biomass Ptoduction 92.7 P_H-H~PowerPlanI 95.0

BT·Biomass Transport 99.2 TL - Transmission Iinc 94.0

BL ·BiomassLiquefaction 60.0

LR· Syncrudc RcfinCl)' 87.4

RT·Rcfinod Transport 99.2

Sctvicc Station 48.2 WallOudct 893

intema1 CombustionEnginc Vchicle (lCEV) 19.8 E1cctric VchicIc (EV) 70.4

n .. '''"' 9.511 " "'

62.9


•

•

Table 4.15 Frrst and Second Principle efficiencies for ICEV and EV different configurations.

1995 2010Configuration

E'lJ E 'lJ% % % %

A Petroleum - ICEV 12.1 28.1 16.5 38.4

B. Petroleum - EV 8.3 19.3 23.6 54.9

C. Biomass - EV 5.0 13.8 10.2 28.3

D. Biomass - ICEV 19.4 16.3 9.5 26.4

E. Natural gas - ICEV 8.3 19.3 25.7 59.8

F. Coal- ICEV 7.4 17.2 11.7 27.2

G. Coal-EV 9.2 21.4 25.1 58.4

H.Hvdro-EV 27.0 28.4 62.9 66.2

corresponding to the Iùghest SPT efficiency as weil. The second Iùghest FPT efficiency is the

traditional configuration A (petroleum and lCEV);

(ù) The SPT efficiency ofconfigurations A and H are not much different in spite ofthe

greater discrepancy in the FPT efficiencies for these two configurations. This is due

to the faet that the exergy content in the hydro potential is higher (95%) !han in

petroleum (43%);

(JÜ) On the other band the configuration with minimum FPT and SPT is C (biomass and

electricity).

(i) The configuration with the highest FPT efficiency is H (hydro electricity and EV)

Regarding the forecasts for the year 2010:


Table 4.16 Electric energy production for cliffcrent fuel types in Canada. 1()92.

78

•

•

Region Cool Oi!Natural

Nuclear Hydro Othcr TotalGas

1. Canada 16.7 2.7 2.2 15.2 62.2 l.l 100.0,

2. Newfoundland 0.0 4.9 0.0 0.0 95.1 0.0 100.0

3. P.E.!. 0.0 100.0 0.0 0.0 0.0 0.0 100.0

4. Nova Scotia 61.7 27.5 0.0 0.0 9.2 1.6 100.0

5. New Bnmswick 7.5 41.9 0.0 30.3 18.6 1.7 100.0

6. Québec 0.0 0.8 0.0 3.1 96.1 0.0 100.0

7. Ontario 19.8 0.5 1.7 48.1 28.7 1.3 100.0

8. Manitoba 1.0 0.0 0.0 0.0 98.8 0.2 100.0

9. Saskatchewan 70.5 0.3 6.3 0.0 21.6 1.3 100.0

10. Alberta 81.4 0.0 12.4 0.0 3.3 2.9 100.0

II. British Columbia 0.0 0.5 2.6 0.0 94.5 2.3 100.0

12. Yukon and N.W. T. 0.0 25.7 9.0 0.0 65.3 0.0 100.0

5omee. [Canada, 19921.

(i) An configurations that use EV(B, E, G, H) with the exception ofbiomass have higher

FPT and SPT efficiency than the traditional option ofcrude oil and ICEV;

(Ji) Again configuration H bas the higilest FPT and SPT efficiencies among the

configurations studied;

(IÜ) The re1ative difference between the FPT efficiencies is much higher than between the

correspondïng SPT efficiencies;

(iv) It is ÏDteresting to note that configuration A (petroleum and lCEV) is less efficient

than configuration B (petrolewn and EV), indicating that, ifother restrictions will not

apply (such as car autonomy or cost ofthe e1ectric vehicle) the EV will be certainly


Table 4.17 EV efficiencies in the Canadian provinces.

79

•

•

EV EfficiencyConsidering Generation:Mix (%)

Region1995 2010

1] E 1] E

1. Canada 20.3 24.7 45.7 57.3

2. Newfoundland 26.1 27.8 60.3 64.3

3. P.E.!. 9.4 16.3 9.5 26.4

4. Nova Scotia 10.8 20.5 24.1 49.8

5. New Brunswick 12.6 18.9 20.6 36.2

6. Québec 26.3 27.9 60.8 64.7

7. Ontario 14.4 20.8 28.2 44.8

8. Manitoba 26.8 28.3 62.4 66.1

9. Saskatchewan 12.9 22.7 33.1 59.7

10. Alberta 9.6 21.2 26.0 58.0

11. British Columbia 25.9 27.7 60.4 64.9

12. Yukon and N.W. T. 20.8 24.5 45.8 55.4

wide1y adoptee\, even in utilities with only thermoe1ectric power plants;

(v) The ICEV bas a much widervariation in their SPT efficiencies than the corresponding

EV alternatives.

Table 4.16 shows the generation mile in 1992 for different Canadian provinces [Canada

1992]. Note that hydroe1ectric resources account for approximate1y 6()O/O ofthe primary

eneIgy use for e1ectric generation. In five ofthe Canadian provinces, petroleum constituted

more than 25% ofthe generation mix. However, in the remaining provinces petroleum always

represents less than 5% ofthe generation mile.


•

Table 4.17 shows for the EV, the FPT and SPT efficiencies for the Canadian provinces for

1995 and for 2010. Note that, provinces with a high percentage ofhydro generation such as

NewfoundIand, Québec, British Colwnbia and Manitoba have lùgher efficiencies than the ones

with high concentration of fossil or nuc1ear power plants. The overall FPT and SPT

efficiencies for Canada in 1995 are respectively bigger and smal1er than the corresponding

configuration A (petroleum and ICEV). On the other band, comparing the corresponding

values for 2010, the EV in Canada is, by both FPT and SPT perspectives, more efficient than

the configuration A (Table 4.15).

4.4.4 Petroleum displacement by EV

EV's are potentially effective displaœrs ofpetroleum becallse, in Canada, in general, much

ofthe e1eetricity generation is hydroeIeetric. The amount ofpetroleum displaced is calculated

by:

1 Poil- - ----=----d = _T)...:;A,--_T)-,P;...-~o_T)-=:FT=--T)..;;;CF,--T),;;;CT,--T)~CR

1

1JA

(4.21)

•

where T).. is the FPT efficiency ofthe configuration A, Pail is the proportion of oil in the

generation mix and T)p_o, TJn, TIen 1l:r, 'rh equal the FPT efficiencies ofthe thermoe1ectric

power plant, fuel oil transport, crude refinery, crude transport and crude recovery,

respectively.

The amount of petrolemn displaced as a proportion oftbc amount used in road transportation

fortheyears 1995 and 2010 is shown in Table 4.18. The amount ofpetroleum displaced for

Canada would be at least 96% in 1995 and 97.7 % in 1995 and 2010. In other words, each


Table 4.18 Petroleum displacement by the adoption ofEV in 1995 and 2010.

81

•

•

Petroleum displacement by the adoption ofEV,

Region %

Year 1995 Year2010

1. Canada 96.0 97.7

2. Newfoundland 92.8 95.9

3. P.E.!. -46.2 16.2

4. Nova Scotia 59.8 76.9

5. New Brunswick 38.8 64.9

6. Québec 98.9 99.4

7. Ontario 99.3 99.6

8. Manitoba 100.0 100.0

9. Saskatchewan 99.5 99.7

10. Alberta 100.0 100.0

11. British Columbia 99.2 99.6

12. YukonandN.W. T. 62.4 78.5

Joule ofthe road transportation end-use performed by an EV will displace 25 times more

petroleumin 1995. The corresponding rate for the year 2010 is 1:43. Note, however, that for

P.E.!. the adoption ofEV in 1995 will not represent an economy in the use ofenergy and

neither itwill displaœ petroleum. The reasons for these are: 1000/0 ofthe electricity in P.E.l

is generated by petroleum and the ICEV configuration A being more eflicient than

configuration B (lCEV and petroleum). However, by the year 2010, even in P.E.l, a switch

to EV's would lead to petroleum displacement.


4.4.5 Energy supply for EV

82

•

•

The possible sources ofenergy to supply the eventual increase in the demand ofe1ectricity by

EV could he provided either by:

(i) Increasing gene.-ation;

(n) Improving in the system 1000 fàctor;

(ili) Improving ofthe system FPT and SPT efliciencies;

(IV) A combination ofthe previous alternatives.

-. lŒY ...r ~ n -,... -[ F_ ... , EV f--.

Fod_ r

1~ ... DH ~R - 1 '

,.

~

*', lit

~~H-,1-... ...,. ~

El ...~,. H,op

lCEl' -11IICmai"""'-...agi"" vchIckEV- c/M:trlc vchIckDlf - dINCt8poœ1walIngjùnrot:cSb - cIM:trlc bœcbocrd_~ - J.«-J1IDIfPtzlNo-air

p-ga- J.«-J1IDIfP,..,...wo-alr

• - CO'u-.::tlcm:

FJgUre 4.10 Two natural resources and end-use mode!.


•

•

Table 4.19 Percent ofelectric energy consumption above the present level due to by EV inthe Canadian provinces, in 1995 and 2010.

Percent ofelectric energy consumption represented

Region byEV

1995 2010

1. Canada 55.2 23.0

2. Newfoundland 9.8 4.2

3. P.E.!. 8930.7 3115.1

4. Nova Scotia 43.4 16.4

5. New Brunswick 92.0 35.1

6. Québec 31.8 13.6

7. Ontario 106.4 41.8

8. Manitoba 28.7 12.3

9. Saskatchewan 126.1 49.4

10. Alberta 150.6 55.7

Il. British Columbia 41.3 17.7

12. Yukon &. N.W.T. 76.6 31.8The eud-usc road·traDsportatiOll was CXlIlSidt:Rd to bc COIlSlllnt for the pcriod 1995-2010.

The first three alternatives are discussed now.

• Increase in the Generation Supply

The necessary increase in electricity demand due to EV is shown in Table 4.19 for Canada

and its provinces. Note that, for Canada, in the year 2010, the supply of a11 road

transportation byEV represents an inaease of23% in electric energy production with respect

to today's level. The corresponding value for 1995 is 55% due to the filet that today's EV is

not as efficient as forecasted for the year 2010.

• Applications of Exergy Analysis in Eleetric Energy System Planning 84

•

•

Table 4.20 Yearly consumption ofspace heating alternatives and electric energy conservedto replace an e1ectric baseboard.

Space Heating Alternatives Consumption Electric energy conserved toinkWhlyear replace an e1ectric baseboard

kWhlvear

1. Heat Pump Air-to-Air 9,000 6,000

2. Heat Pump Ground-to-Air 5,100 9,900

3. Direct Oil or Gas Heating 18,518 15,000

• Improvement in the load factor

The road transportation load in Canada could he supplied entirely by the 1995 power system

capability ifEV were adopted massively by the year 2010 and if the system load-factor

Canada from the existing 65.7"/0 to 80.8%. In those Canadi'311 provinces rich in hydro

resources such as Québec, Newfoundland, Manitoba and British Columbia the required

increase in the load-factor in the year 2010 will he 8.4%, 2.8%, 7.6% and 11.5%,

respectively.

Because ofthe difficulty ofensuring that the recharging ofthe batteries will occur in off-peak

hours, some economic incentives must he introduced, such as time-of-use tariffs.

• Energy and exergy conservation

FmaIly, the use ofmore ex:ergetically efficient space heating alternatives will release e1ectric

power for EV road transportation. Figure 4.10 shows an energy system used to study this

type ofDSM strategy.

Almost fifty percent ofthe forecast demand for 1995 in Québec represents e1ectric loads at

low temperature (e.g., space heating). The demand for low temperature heat represents at


•

•

Table 4.21 Savings cbaracteristics 10 replace e1ectric baseboard heater by more exergeticallyefficient options in terms ofroad tran.>-portation end-use in 1995 and 2010.

Driving distance (D) Equivalent gasoline

Space Heating with a sub-compaet (EJ savings,Alternatives EV, in kmlyear in litreIyear

1995 2010 1995 2010

1. Heat Pump Air-to-Air 17,143 30,000 1,749 2,239

2. Heat Pump Ground-to-Air 28,286 49,500 2,886 3,694

3. Direct Oil or Gas Heating 42,857 75,000 3,192 4,415

least 16,000 MW in 1995 andisexpected 10 reach21,500MWbytheyear 2010. The fraction

of the use ofe1ectricity for low temperature applications in Québec is expected to remain

practically stable up to the year 2010 [Hydro-Québec, 1993].

As seen in section 4.2, space heating alternatives are much less efficient ifaccording to the

8PT than the road the transportation. A simple example could illustrate this more clearly.

Consider Figure 4.10 that shows a system with two end-uses (road transportation and space

heating) and two primaIy energy sources (oil and hydro potential). Note in Figure 4.10, that

the end-use road transportation could be supplied by either EV or ICEV and the end-use

space heating could be supplied by space heating furnace, e1ectric baseboard, air-to-air heat

pump or ground-to-air heat-pump.

Considering that the space heating end-use requirement ofa given dwe1Iing is supplied by a

e1ectric baseboard, the space heating load will be 15,000 kWhlyear, Le., 5 kW per 3,000 h per

year and the FPT efficiency ofa baseboard cao be considered as 100"/0.


Table 4.20 shows the amount of electric energy conserved if electric baseboards were

replaced by more exergetically efficient space heating options. Table 4.21 presents the same

information as the previous table but in terms ofdriving distance with a EV subcompact car

in 1anIyear and equivalent gasoline savings in litre! year for the years 1995 and 2010.

The driving distance, D was calculated by applying:

(4.22)

•where E. is the electric energy displaced by adopting more exergetically efficient space

heating alternatives and <;v is the EV consumption given in Table 4.10.

The equivalent gasoline saving, shown in Table 4.14 is,

DE =--

q CJCEV

np

T)DH C(4.23)

where ~CEV is the lCEV consumption given in Table 4.10, T)DIl is the direct heater FPT

efficiency, c is a constant to transform kWh to kJ, n is the number ofhours ofutilization of

the space heating device per year and p is the end-use space heating power.

The Iast term ofequation (4.23) ooly applies for the direct space heating option. Clearly, it

is possible ta see through this example that by changing space heating from baseboard to any

the other altemative will result in sorne savings. The direct gas or oil space heating alternative

will however, save the most, either in driving, distance as weil as in equiva1ent gasoline in

litres per year.

• Applications of Exergy Analysis in Electric Energy System Planning ô7

•

•

Extending the same reasoning to the whole province, the equivalent amount ofspace heating

in Québec that would have to be converted to direct space heating in order to make e1ectric

power available to supply the whole road transportation end-use in the year 2010 in Québec

is around 27%.


4.5.1 Limiting levels ofSPT and FPT efliciencies

The Iimiting 1eve1s ofthe main five end-uses were studied inc1uding: traction, Iighting, water

heating, cooking, space heating. The limiting 1eve1s were ca1cu1ated for aIl possible system

CODfiguratiODS for the following natural resourœs: hydro potential, nuc1ear energy, petroleum,

natura! gas and coal. These levels are benchmark Iimits which cannot be exceeded by any

alternative with the assumed technology efiiciencies. It was shown that, in generaI, it is not

possible to maximize simultaneously the First and the Second Principle efiiciencies.

4.5.2 DSM performance improvement induding cross-efTects and

eurgetic anaIysis

·Demand SideManagement Performance Improvement (PI) programs in the residential sector

must considercross-elfects as these can sharply reduce the overa1l impact ofthe program as

viewed from the perspective ofthe dwelling. Thus, although there can be a savings at the

appliance leveI, increased beating loads reduce the overa1l savings.

This impact varies significant1y among the different levels ofan energy system (appliance,


•

customer, electric utility, ail or gas utility and natura! resources). For example, the electric

utility can save an important amount ofenergy, however, the oil/gas utility will see its demand

increase so that the overall savings in natural resources are not as significant as expected.

Different energy system configurations have a major influence on the amount of savings at

various levels ofthe system. A number ofextreme cases ofsuch configurations were tested

in this thesis including two kinds ofelectric generation combined with three types ofspace

heating devices. Configurations with a mixture ofenergy sources are the most susceptible ta

gain from PI measures.

The evaluation of PI measures should include exergetic as weil as energetic analysis.

Exergetic analysis is particularly important in evaluating the impact ofPI measures in the

residential sector since most ofthe measures will generate cross-effects on heat-related loads.

Since these loads are not necessarily supplied by the same source ofenergy, their exergetic

content is different. This distinction cannot be detected by the FI1'st Principle of

Thermodynamics and it bect-mes necessary to make a comparison on the basis ofthe Second

Principle.

4.5.3 Electric vehicles and exergetic analysis

Eigbt configurations ofenergy supply for EV and ICEV have been studied. SPT analysis for

1995 shows that the configurations A (petroleum and lCEV) and H (hydroelectricity and EV)

had approximately the same efliciency for 1995, that is, around 28%, However, by the year

2010, configuration H will have much bigher efliciency than configuration A

EV technology will most probably drastical1y decrease the amount ofair emissions since, even

in the case ofthe coDfiguration ofEV that utilizes thermoelectricity, its efliciency is forecast

• to he much bigherthan the traditiollll1 configuration ofpetroleum and lCEV. In other words,


•

•

EV technology will provide much iower air emissions than the traditional ICEV in any ofthe

configurations ana1ysed. In addition, EV will permit much greater f1exibility in terms offue~

since power plants can use a wider range offuels than ICEV.

The necessary increase in the electric energy to supply the EV's could be met by:

(i) The improvement of the system load factor. Since car batteries take tirne to be

recharged, this type ofload is a good candidate for tariffstrategies like tirne-of-use

or type-of-use'. It was shown that an improvement in the Canadian power system load

factor from the existing 65.7% to approximately 80.8%, by the year 2010, is enough

to supply the tota1ity ofthe road transportation EV load.

(ü) DSM strategies. It was demonstrated through an example that the changing ofthe

space heating devices to more SPT efficient ones will contn"bute significati....e1y to

provide energy for the adoption ofe1ectric vehicles.

(iü) Increasing in power generation. A 23% increase in e1ectric generation will suffice to

supply the whole Canadian road transportation f1eet by the year 2010.

1 These type oftariffs will he discusscd in Chapter 6.

•

•

Economie and Exergetie Optimization Analysis of Space Heating Systems

Chapter 5.

Economie and Exergetic Optimization Analysis

of Space Heating Systems

5.1 Introduction

•

Cbapter 3 of this thesis presented a general energetic and exergetic mode! of an e!ectric

energy system, the principles ofoptimizarion oftbis mode\, as well as an illustrative example

of system planning with multiple optimjzarion goals. The present chapter applies these

optimization principles in greater detail to a more realistic space-heating problem. This

problem is iirst analysed from the Fust and Second Principle of Thermodynamics by

minjmjzing the total energetic and exergetic use at the natura1 resources leve!. The minimum

energy and exergy solutions are then compared with the minimum cost designs. Fmal1y,

diffdent types ofcost incentives are studied with the intent offorcing the minimum cost and

90

• Economie and Exergetie Optimization Analysis of Space Heating Systems

minimum exergy solutions to coincide.

91

The importance ofoptimization1 is its ability to systematically find feasible designs among

the infinite choices that satisfy a given set ofequaIity and inequaIity constraints and at the

same time, minimize a predetermined objective function. A generaI objective function can be

defined which assigns different weights to each natura1 resource and energy conversion

device so that,

(5.1)

•

•

where R is the set ofnaturaI resources and Disa set ofenergy conversion devices. The last

term ofequation 5.1 descnbes the cosf to the customers. Other, even more generaI objective

functions can be formulated by assigning a weighting factor to each energy and exergy state.

Such formulations permit the planner to assign different values to each individual resource,

including the possibility ofdifferentiating between energy and exergy. As an example, an

energy policy may assign a higher value to oil, relatively to other resources, becanse ofits

scarcity, greater environmental impact and its dependence on foreign imports.

As discussed in chapter 3 and demonstrated in severaI examples in chapter 4, in many

situations the minimiZlltion ofone ofthe above variables does not necessarily correspond to

the minimization ofanother. Thus, a compromise must be made by the planner to ensure that

an acceptable balance among all variables is reached.

1 In this thesis, all the optimiZllrion problems are solved with the Matlab

OptimiZlltion Toolbox [Grace, 1992].

2 Cost can assume different fonDS, such as, cost to the customers, to the utilities orto society.

• Economic and Exergetic Optimization Analysis of Space Heating Systems 92

•

•

The relevance of such optimization studies resides in allowing the planner to better

understand the system behaviour under different conditions. Although the solutions provided

by the optimization algorithms are most Iikely not to be found in the real world by reasons

difficult to mode! such as human preferences, optimal solutions do outline the system

behaviour under ideal conditions. The solutions provided by such optinùzation studies are like

landmarks, estabüshing limits for planning plhl'0ses under different objective functions.

5.2 Space Heating Mode!

Section 4.1 presented an energetic and exergetic analysis of a space heating system.

However, this analysis was carried out without optimizing the system variables. The present

section, therefore, analyses this system by optimizing energy and exergy variables combined

with economic considerations.

The application of optïmization techniques to the planning of heat re!ated end-uses

(particularly space-heating) is important in exergetic analysis for the following reasons:

(i) There exist many space heating system alternatives because ofthe wide spectrum of

possible energy sources and energy conversion devices and they should be assessed;

(ù) Heat re!ated loads usually have a wide difference between the FPT and SPT

efiiciencies;

(m) To make an intelligent choice among the many alternatives, a systematic approach is

required. Such a choice may favour a design alternative which does not necessarily

•

•

Economie and Exergetie Optimization Analysis of Space Heating Systems

<, ,--. <1r--::....-----------~ DB

<F < pp_tk BB

<J7l HP_""

H <~I PPjty t-J HP;<4

Figure. 5.1 Space beating model.

bave the bigbest FPT efliciency but wbicb bas a bigb SPT efliciency;

93

(iv) SimiIarIy, the minimnm cost design witb the existing electricity tariffs and fuel priees

sbould he compared with other designs wbicb maximize FIl"St and Second Principle

efliciencies.

•

Figure 5.1 presents a model witb only one end-use, namely the overall space beating

requirements, (Q) and two naturaI resources, bydro resources (II) and fossi! fuel (F). The

fossil fuel resources feed bath the direct beating energy conversion (DR) equipment and the

thermoelectric power plants (pP_th), while the bydro resources (II) are used for electric

powergeneration tbrougb thebydro power plants (pP_by). In tbis mode\, four space beating

alternatives were considered:

(i) Direct fossi! fuel (DR);

(u) Eectric baseboard (BB);


(iii) Electric air-to-air heat-pump (HP_aa);

(iv) Electric ground-to-air heat-pump (HP...sa).

94

To perform the optimization ofthe space heating mode! shown in Figure 5.1 it is necessary

to build the set ofequations that charaeterize this problem, that is,

•

(5.2)

(5.3)

(5.4)

(5.5)

The equivalent A matrix and b veetor are given by,

1 1 1 1 0 0 0 0

1 0 0 0 0 0 0 -11')DH

A= 01 1 1 -1 0 0 0

(5.6)-1')BB 1')HP-... 1')HP-gc

0 0 0 01 0-- 1')PP-th 1')pp.hy

1')77

•


b=[Q 0 0 0]'

where the symbol " . " , in equation 5.7, denotes the transpose ofthe vector.

5.3 Economie Analysis of Space Heating

95

(5.7)

•

•

Table 5.1 presents the necessary input economic and other relevant data for the analysis of

space heating options. The foUowing comments apply to each row ofthe table:

(1) The capital cost for the alternative e1ectric baseboard is the cheapest. The alternative

ground-to-air heat pump bas the highest capital cost and it represents more than 34

rimes the corresponding cost ofthe baseboard alternative. It must also be noted that

the capital cost figures shown for the heat-pumps correspond to 75% ofthe aetual

cost ofthe device as the remaining 25% is associated with the cooling mode ofthe

heat-pump;

(2) The Iife expectancy ofe1ectric baseboards is assumed to he the longest since the other

options have more moving parts and are more like1y to fiIil;

(3) The opportunity cost rate is the interest rate, on a yearly basis, that would be earned

above inflation ifthe capital spent had been invested in the market;

(4) The efficiency or coefficient-of-performance varies significantly, ranging from 81%

( for direct space heating ) to 300"/0 ( for heat-pump ground-to-air ). Note that the

e1ectric baseboard option is assumed to have an efliciency as measured by the FIISt

Principle of 100%, since it is assumed that ail e1ectric energy is converted to low

temperature heat;

• Economic and Exergetic Optimization Analysis of Space Heating Systems 96

(5) The priee offuel to the customers is around 177% of the fuel priee to the thermal

power-plants. In t1ùs study, it is assumed to be the same for ail three regions

considered;

(6) The energy escalarion rate per year is the increase above inflation ofthe fuel costs and

electricity tariffs;

(7) Direct spaee heating and the ground-to-air heat-pump alternative have the Iùghest

maintenanee rates ( percentage ofthe initial capital cost per year );

(8) The number ofhours ofoperation was assumed to be constant at 3,000 hours per year

for ail spaee heating alternatives considered;

Table 5.1 Relevant economic data for di1ferent spaee heating alternatives.

t Source: [Stalistics Canada, 1992]• CocfliCtCllt ofpcrfonD8llCC

Space Healing AltemaliveE1cctric Hcat.pump Heat'plDDp Di=t space heating

BaseboanI air·to-air ~.to-air

1. Capital cost 49 8S7 1,713 117(S/kW ofend·use)'

2. Lifc cxpcctancy (years) 20 15 15 15

3. Opportunity cost rate4.0

~/o/year.)

4. Eflicicncy ~/o) 100 170' 300' 81

5. Oilpricc4.8 SIG] (17.4 $IMWh) 8.5 SIG] (30.7 $IMWh)

(for thermal power-plants) (for customas)

6. Encrgy cscaIation rate2.0

~/olyear)

7. MainttTumœ1.0 1.5 2.0 2.0

~/o ofcapital cost1year)

8. Operation (hours 1year) 3.000

9. E1cctric rate,Québec, 6.52Ontario. 9.56(c/kWh)t New York. 16.56 ..

: Canad·anS

•

• Economie and Exergetie Optimization Analysis of Space Heating Systems 97

•

(9) Finally, for comparison purposes, clifferent e1ectric rates were consideree! for three

geographical locations: Québec, Ontario and New York. Because of the

preponderance ofhydro e1ectricity in Québec, the e1ectric rates in Ontario and New

York are respectively around 47"/0 and 154% higher.

Note that the parameters in Table 5.1 are representative and can be alteree! to simu1ate other

conditions.

Before optimizing the various design alternatives, it is useful to examine the Iife costs ofthe

space-heating options at the customer level. The term Iife cost represents the cost to the

customer for the expected Iife ofthe space heating device including, capital, maintenance and

operational costs. The capital cost includes the initial investment and the opportunity cost.

The operational costs invo1ve, both the maintenance and the energy costs (based on fuel rates

or e1ectric tariffs).

The Iife cost~ in today's doUars ofa given end use device i producing yearly useful energy,

t; , in kWhlyr, is given by,

(5.8)

•where IC; is the initial capital cost in $/kW ofend-use energy, q is the number ofhours of

operation peryear,1ti is the load filetor ofthe device elCpiessed as some dimensioDless fraction

ofone, p is the opportunity cost rate as a fraction ofthe initial capital, Ill; is the maintenance

cost per year as a fraction ofthe initial capital cost, fi is the e1ectric tariffOf fuel rate in


•

$/kWh, ~ is the ecpected number ofyears in the Iife ofthe device and 5 is the expected energy

cost escalation rate as a fraction ofone. Finally Tli is the FPT efficiency ofthe device.

Equation 5.8 is important becansc it discriminates among the various components ofthe cost

ofa device in terms ofits economic variables and energy consumption. Equation 5.8 is aIso

needed to define the cost components ofthe optimization criterion f given by equation 5.1.

Note that the cost ofa device is current1y a1ways rationalized in terms ofits energy and power

consumption. In other words, exergy bas been virtually ignored in economic analysis.

By dividing the life cost, Lei' by the life expectancy in years, ~ and by the amount ofenergy

that the device will consume per year, ~ , one obtains the average cost ofthe device over its

life time, in $/kWh, ac; , where,

(5.9)

Therefore, the cost term appearing in the objective fimctions defined by equation 5.1 is ofthe

forro,

(5.10)

•where Ci is in $/yr. The results ofan ortïrni7lrtion are usually summarized through the average

cost ofail end-use devices, narneIy,


Lac, e,ac = .,:D===__

Le,D

99

(5.11)

Note that the variable, 1IG, in equation 5.9 can be divided into two components, capital cost,

ie; and operation/maintenance cost, olD; ,

•where,

and

oc, = ic, + am,

l,

le 7, L(l+sY__, Cm 1) + .......f!.:·.:,.!__n lÇ' 1 1

1 ~I 1'),ami = ..L..:...::-=- ----::.-_LI,

(5.12)

(5.13)

(5.14)

•Note that the 1irst term in the equatïon 5.14 represents the maintenance cost and the Iast term

represents the energy costs.

Table 5.2 shows the average life costs for several alternatives consideree! for the space

heating system ofFigure 5.1. Note that, striet1yfrom the economic point ofview, in Table 5.2


Table 5.2 Average life costs to customers for different space heating alternatives.

the direct space heating alternative is the most economic one for the customer in terms of

life costs either for Québec. Ontario or New Yorlc. The alternative electric baseboard is the

most expensive for any ofthe three regions studied except in Québec. This occurs in spite of

the initial cost ofthis alternative being around 42% cheaper!han the direct space heating

option. Finally. the life cost of the heat-pumps are 2 to 32% cheaper in New York and

Ontario compared to the electric baseboard option, but 1 to 28% more expensive!han the

baseboardoption in Québec.

'CanadienS

Space Heating AItemalivcDirect space Eloeme Heat-pump Heat-pump

heating Baseboard air-to-air ground-to-air

New5.00 20.72 15.31 14.49York

1. Average lifc c:osts'(clkWh ofend-use) Ontario 5.00 12.04 10.47 11.74

Québec 5.00 8.27 8.37 10.55

New100 414 306 290York

2. Average lifc costs ("/0)1(Direct space heating =100) Ontario 100 241 209 235

n. .•~ 100 165 167 211..t Source: (Stal1SliCS Canada, 1992]

•

Tables 5.3, 5.4 and 5.s present the average life cost separated into energy, maintenance and

capital costs ofthe different space heating alternatives in New York, Ontario and Québec,

respective1y.

Note in Tables 5.3, 5.4 and 5.5 !bat:

•(i) The energy cost for direct space heating represents 89"10 ofthe life costs. For the

e1ectric baseboard the energy cost represents more !han 97% of the life costs

regardless ofwhere it is located, i.e., New York, Ontario or Québec. For the heat-

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Economie and Exergetie Optimization Analysis of Space Heating Systems 101

Table 5.3 Energy, maintenance and capital average costs at the customer level fordifferent space heating options for Ontario.

Direct Electric Heat-pump Heat-pumpSpacc Heating Alternative Spacc Bascboard air-to-air ground-to-air

Heatinl!

1. Encrgy costs, clkWh 4.45 11.84 6.61 3.74

("10) (89.0) (98.3) (63.1) (31.9)

2. Maintenance costs, clkWh 0.08 0.02 0.43 1.14

("10) (1.6) (0.2) (4.1) (9.7)

3. Capital costs, clkWh 0.47 0.18 3.43 6.86

("10) (9.4) (1.5) (32.8) (58.4)

4. Total, clkWh 5.00 12.04 10.47 11.74

("10) (l00.0) (l00.0) noo.O) noo.O)

Table 5.4 Energy, maintenance and capital costs at the customer level for different spaceheating options for New York.

Spacc Heating Altcmativc Direct Spacc Elcctric Heat-pump Heat-pumpHeatinl! Bascboard air·to-air l!rOUIId·to-air

1. Encrgy costs, clkWh 4.45 20.52 11.45 6.49

("10) (89.0) (99.0) (74.8) (44.8)

2. Majntc:nmœ costs, clkWh 0.08 0.02 0.43 1.14

("10) (1.6) (0.1) (2.8) (7.9)


("10) (9.4) (0.9) (22.4) (47.3)

4. Total, clkWh 5.00 20.72 15.31 14.49

(%) noo.O) noo.O) noo.O) noo.O)

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pump spaœ heating alternatives the energy costs represent around 24 to 75% oflife

costs ofthe device;

(u) The maintenance costs represent between Jess than 1% ( e1ectric baseboard) to around

10% ( heat-pump ground-to-air in Québec) of the Iife cost of the space heating

alternative;

(Iii) The capital cost ofthe direct space heating alternative is 9.4 % ofthe Iife-cost ofthis

alternative. However for the heat-pump space-heating alternatives the capital costs

represent always a significant proportion oftheir Iife cost, ranging from 22.4% to

65.0"/0. On the other band, capital COsts represent only a smalI fraction, Jess than

2.2%, ofthe Iife cost ofthe e1ectric baseboard alternative.

Table 5.5 Energy, maintenance and capital COsts at the customer Jevel for different spaceheating options for Québec.

Direct Eicctric Hcat-pump Hcat-pumpSpllCC Hcating Alternative SpllCC Bascboard air-to-air ground-to-air

Hcatinll

1. Energy costs, clkWh 4.45 8.07 4.51 2.55

(%) (89.0) (97.6) (53.9) (24.2)

2. Maintenance costs, clkWh 0.08 0.02 0.43 1.14

(%) (1.6) (0.2) (5.1) (10.8)


(%) (9.4) (2.2) (41.0) (65.0)

4. Total, clkWh 5.00 8.27 8.37 10.55

(%) (l00.0) (l00.0) (100.0) (100.0)

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5.4 Optimization with Mixed Objectives

The space heating system can be optirnized from the points-of-view of cost, energy and

exergy subject to the space heating mode! equations 5.2 to S.S. From the above discussion,

the minimum cost solution is clearly the option with 100% direct space heating. Table 5.6

summarizes these three optimum solutions according to the optimization criterion chosen

assuming that there are no limit on the amount ofspace heat provided by each alternative.

Later in this section, another case is studied with limits on the various heating options.

Thus, the "best design" heating alternative depends on whether cost or energy/exergy

considerations are preeminent. For example, as seen in section 4.1, if the space heating

altematives e!ectric baseboard and direct space heating are comparee!, then the first option bas

the highest FPT efiiciency but the direct space heating bas the highest SPT efiiciency.

In the more realistic case where the outputs ofthe possible space heating conversion devices

are limited, as is the case discussed later on in this section, the best designs may involve

combinations ofan heating devices. In such cases, an designs where onlyenergy and exergy

are considered in the objective function (zero weight for cost), the ground-to-air heat-pump

is normally saturated l:>ecanse from bath the FIrSt and Second Principles, this alternative is

Table 5.6 Best space heating design as a function ofthe minimizarion criterion, unconstrainedcase.

MinimizationBest Design ( Unconstrained )Criterion

1. Cost 100"/0 direct heating

2. Energy 100"/0 hydre power plants + 100% ground-to-air heat-pumps

3. 100"/0 hvdro llOwer Dlants + 100"/0 2I'Ound-to-air heat-DumDs

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Table 5.7 Optimization criterion and objective function considered for the space heatingmodel ana\ysis.

1Optimization Criteria

1Objective Function

1

1. Energy ea

2. Exergy xR

3. Cost Co

4. Energy and exergy ea+xR

5. Energy and cost w\ ea +Co

6. Exergy and cost W2XR +Co

7. Energy, exergy and cost w\ (ea +w2xJJ + Co

8. Cost with subsidies Co(6)

more efficient than ail others. Mer saturating ground-to-air heat pumps, the other

alternatives will he selected in accordance with the objective function and the constraints

chosen. In such cases, the minimum energy and exergy designs are norma1ly not necessarily

equal.

The combination ofenergy and exergy together with costs as optimiZlltion criterion gives

further insight when comparing space heating alternatives. The mixed optimiZlltion criteria

considered for the space heating mode! ana\ysis are \isted in Table 5.7. Note that ea and Xst

represent respectively the amount ofeneIBY and exergy consumed at the resource IeveI while

Co is the cost to the customer ofthe end-use energy conversion devices. In Table 5.7, the

variable r represents the fuel or e!ectric rate in clkWh charged to the customers. The explicit

dependence ofthe cost Co on r is described in equation 5.9. Note, as weIl, that optimization


criteria one and two in Table 5.7 are equivalent to maximizing the FII'St and the Second

Principle ofThermodynamics efliciencies. Criterion four in Table 5.7 minimizes with equal

weight bath the exergy, "R, and the energy, ea , consumed at the resource leve1. Optimization

criteria four, five, six and seven combine with different weights energy and exergy at the

resource level together with the cost to the customers. The optimization criterion eight takes

into consideration the minimization ofthe subsidized cost to the customers, <:0(6), where 6

is the parameter representing the given subsidy, ofwhich three have been consideree!, fuel

rates, initial investment and opportunity costs.

•The space heating model was again optimized for the criteria shown in Table 5.7 but, this

time, considering the constraints. These were chosen as typicallevels in a fossi1-fuel-based

utility:

Table 5.8 Optimum energy states for diffèrent optimization criteria.

t UpperbouDd Iimit rcachcd.Q =spccificd OVtnll spacc-hcating IeqUIICIIlCIIts

Optimi7JItion Criteria Min Min Min Min<:0 "R ea (ea + "R>

StatesEnd-use energy

(%ofQ=)

Ct (end-usedi=thcating) 100.0 95.0 66.3 85.0

e:(end-use cleclric bascboard) 0.0 0.0 18.7 0.0

e, (end-usehcat-pump air-to-air) 0.0 0.0 lOt 10.Ot

c. (end-use hcat-pump ground-air) 0.0 5.0t 5.0t 5.0t

e, (cleclric load) 0.0 1.7 26.2 7.6

Ca (fuel for thcrmaI power-plant) 0.0 0.0 0.0 0.0

c, (hydro potential resoun:es) 0.0 1.9 30.0t 8.6

Ca (fuel for di=t spacc hcating) 123.5 117.3 81.9 104.9

ea(tolal encrgy COIISumptiOll at lIlItlIral :œsowcc Icvcl) 123.5 119.2 111.9 113.6. . . .•


(i) The maximum values ofthe air-to-air heat-pump, ~. and ground-to-air heat-pump,

e., were 5% and 1(lOlo ofthe value ofthe overall specified space heating requirement,

Q, respectively;

(ù) The hydro potential state, e" was limited to 30% ofQ;

(iii) The remaining states were not constrained;

Tables 5.8 and 5.9 shows the simulated values ofthe energy and exergy states ofthe space

heating problem for some ofthe optimization criteria listed in Table 5.7. Analysing Table 5.8

and 5.9 note that,

•(i) In contrast to the unconstrained case ( see Table 5.6 ), in the constrained case the

optimum solutions for a minimum "R or minimum l:tt or even minimum (XR+ eJ are

Table 5.9 Optimum exergy states for diftèrent optimization criteria.

TUpper houDd limit reachcd.

Optimi7))tion Criteria Min Min Min Minc,., XD e" (e" + xD)

States End-use exergy(%ofQ:J

Xl (end-use direct hcating) 2.7 2.6 1.8 2.3

X: (end-use c1cetric bascboard) 0.0 0.0 O.sT 0.0

Je, (end-use hcat-pump air-~) 0.0 0.0 0.3T 0.3T

X. (end-use hcat-pump ground-air) 0.0 O.lT O.l! O.lT

les (clcetric load) 0.0 1.6 24.9 7.2

Xs (fuel for thcrmaI power-plant) 0.0 0.0 0.0 0.0

Je, (hydro potcnIiaI rcsoun:cs) 0.0 1.8 28.st 8.2

"s (fuel for direct spacc hcating) 49.4 46.9 32.8 42.0

1~(tota1~ tion at natural resourcc 1evcI) 4:1.4 48.7 61.3 50.2.•Q- spccificd overall space-hcating reqmremcnts.•

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•


ail distinct;

(ù) The upper bound Iimit ofstate e. ( spaœ heating from ground-to-air heat-pump ) was

reached for ail three optimization criteria This is due to the filet, as seen in Chapter

4, that the ground-to-air heat-pump is more efficient from either the F1I'St or Second

Principle perspectives;

(ùi) The state ~ (heating from electric baseboard) is different from zero ooly when the

optimization aiterion is the minimizatiQn ofthe energetic resources, ea. at the naturaI

resource level In this case, the upper bound Iimit ofthe hydro-potential, e" is reached

as weil;

(iv) The use ofthermaI power plants is never part ofthe solution for ail the criteria tested,

that is, the state e"is always zero. Ifhydro-resources are not available, thermal power

plants will be present to supply the heat-pump requirements ofthe optimum solution;

(v) The minimum cost solution requires ooly direct heating;

(VI) The first four e:.œgy states have re1ativeIy low values, due to the filet that the exergy

in low heat temperature sources is extIemely 10W;

(vii) The energy consumed at the resource Ievel, ea. is a maximum when minimizing cost.

The minimization ofthe end-use cost, Co. leads to the maximum energy consumption

at the naturaI resource, «la. However, the minimization «la leads to maximum exergy

. consumption. However the maximum exergy consumption occurs when minimjzing

«la. This bebaviour is very interesting since it implies that the minimjzarion ofthe cost,

energetic and exergetic resources are conf1icting goals;

Table S.10 presents the average Iife cost te the customer, the F1I'St and Second Principle

eftïciencies and the description ofthe states for five diflèlent optimizariQn criteria for the

regions ofNew York, Ontario and Québec. An the costs' figures shown in Table S.10 are


Table 5.10 Cost and efficiencies ofthe space heating for different optimum criteria.

lOS

•

•

Optimization Region Cost TI € Description orthe statesCriterion (cJkWh) ("10) ("10)

1. Min "" or New 14.49Mine,. or York Ail the space heating front heal.pwnpMin (x.+e,J 262.2 7.54

(Uneonstrained Ontario 11.74 ground-to-air and a11 e1ectrie power

solution)supplied by bydro power plants.

Québec 10.55

New 5.00

2. Mine:" York(Constrained 81.0 5.53 Ail the space heating front di=! oil or

solution) Ontario 5.00 gasheating

Québec 5.00

New 5.48 Heat-pump ground-to-air saturated power

3. Min""York supplied by hydro power plants; the

(Constrained 83.9 5.60 remaining space heating requirements

solution)Ontario 5.34 supplied by di=! fossil fuel space

Québec 5.28heating.

New 9.44 Heat.pwnp ground·to-air and air·to-airYOIk saturBted to the limil, e1ectric bBschoard

4. Mine,. 89.4 4.46 utiJizc up to the limil ofthe hydro power(Constrained Ontario 7.20 plants, the mnBining space heatingsolution) requitenx:nls suppliedby di=!fossil fuel

Québec 6.23 space heating.

New 6.51 Heat-pwnp ground-to-air and air·to-air5. Min (e,.o!?cJ YOIk SBlIIt'8It:d power supplied by hydro power

(Constrained Ontario 5.89 88.1 5.44 plants; the mnBining space heatingsolution) requitenx:nls supplied by di=! fossil fuel

Québec 5.62 space heating.

given in cents ofCanadian doUars per kWh. These costs were calculated over the Iife perlod

ofeach individual device, considering the economic inputs shown in Table 5.1 and equation

5.9. Several points should be stressed about the results shown in Table 5.10. For each

criterion the corresponding comments apply:

(1) For the unconstrained cases, shown in item one, ail three criteria ha~e the same

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•


solution, that is, ail the space hl.:ating requirements are met by ground-to-air heat

pump. The costsforthis case vary from 14.49 to 10.55 cJkWh, corresponding to the

costs of the ground-to-air heat-pump shown in Table 5.2. Note, as weil, that the

variation in the cost is not in the same proportion as the e1ectricity rates in the three

regions studied, since the capital cost for a heat-pump is a major portion ofits average

Iife cost as emphasizerl in Tables 5.3, 5.4 and S.S. Both the First and Second Principle

system efficiencies in this case are the highest among ail the cases tested with values

of262.2 and 7.54 %, respectively. Clearly the unconstrained cases are not normally

rea1izable and are presented only for references purposes. The importance to have

such lderence resides in aIIowing the planner to know the upper bound limits in the

efficiencies, as well as, to compare different end-uses ofenergy from the points of

view ofthe Fust and the Second Principle ofThermodynamics, as it will be shown,

Iater one in the section 5.3;

(2)

(3)

The minimum cost solution requires only direct space heating ( item 2 ) and yields an

aveœge Iife cost of5.DO cents per kWh. Since the oil cost for space heating purposes

was considered te be constant for the regions studied and the minimum cost solution

utilizes only direct heating then the costs for the three regions for this optimum

criterion are constant;

Minimization of the exergy consumption at the resource leveI, is equivalent to

DIaYimization ofthe Second Principle efficiency. Item three shows that e.....x, for the

constrained case, is achieved by saturation with ground-to-air heat-pumps with their

energy supplied by hydroeIectric power generation. The remaining space heating

requirements are supplied by direct space heating devices. Note that the cost for this

aItemative is net signilicant1y different from the minimum cost solution. For any ofthe

three regions, the cost is within 10"/0 ofthe minimum cost solution. The reason for

this, as seen in Table 5.8, is that the minimum "Rand minimum Co solutions difièr only

by the amount ofground-to-air heat-pump which is limited to only 5% ofthe space

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t5 PO

~

s.s~-_':'---~- .... - JIi...-r :- 88

y 13,:,i- 88.... ' .....

.::>

~ 5....

, ~~.. ' , , -, ,

, , , :-84~~~ ' ...' , EfIIcs.ncy

4.S

V: ~2-- "

11 : Il, 4 , '

1 1 80

min cl> min %,. mln(e,. + %.J min e.Opllmlullon ctItotl.

,

FJgl1re 5.2 FII'5t, '1'), and Second, e, Principle efficiencies for different optimization criterion.

heating requirements. Later on, in this section, further discussion is given to design

programs and incentives which induce the maximum e and minimum cost solutions

to coincide;

(4) Minimization of the energy consumption at the resource leveI, is equivalent to

maximization ofthe First Principle efficiency, '1'). Item four shows that '1').... , for the

constrained case, is achieved by saturation with the ground-to-air and air-to-air heat

pumps, some direct-heating as weil as some e1ectric baseboard heaters. The latter are

increased until the hydroeIectric resource 1imit is reached, however no thennoeiectric

generation is required by the optimum solution. The costs, in this case, increase

substantially when compared with the minimum cost solution, (from around 24% to

880/0), depending on the region. The reason ofthis substantial increase is due to the

increased use ofair-to-air heat-pumps and e1ectric baseboards;

(5) Fmally the criterion combining elCergy and energy consumption at the resource level

(Item 5) yields a mixture of the solution reached by items three and four. This

• Economie and Exergetie Optimization Analysis of Space Heating Systems III

-: ;- '

· .. ........ .. . ..· . .· .

. ..- .· . .· .Region

New Yorle8 : :· .

10 : : ..· .

Q.S : :.· .· .

Ontario., .8.S : ":" _._. Ou"bec .: :.... . :

~ 8 : :."'. ~__J.~ : ~

~7.S : .; .; : :- :

'i 7 ~ ~ ~ ~ ~ ;,••~o : : : . .."",._.

/l.S ,......................................... .. ,-. ,· . . ..-. .6 : :~.~ : '~~~~· . . ..~ -,-- ...--..--_.:-,-': :

5_: ~.~..~..~.~..~.~..~..~'~..~.~..~..~.~..~~'\~.ç;;;-~.~::.~-~.-~:~.~-~.-:.~..~.~.:.:..~.~..~.~..~.~"~"~:'~"~'~"~"~'~"~'d'":mln:r" min {l'" + :r~

Opt/maation ~riamin e~

•Figure 5.3 Cost of the space heating for different optirnization criteria, for New YorIc,Ontario and Québec.

optimum solution imposes that all heat-pumps reach their Iimits, with the rernaining

space heating requiIements being provided by direct fossi! fuel heaters. Again, all the

e1ectric power is provided by hydro power generation. Note that the costs and the

efliciencies have intermediate values compared with items three and four as would

be expected.

•

Figures 5.2 and 5.3 SI'l1!IDI!lÏz.etheresults ofTable 5.10 in graphical form. for the constrained

cases. Figure 5.2 shows the FU'St and Second Principle efliciencies. Note that the variations

in 'Il are 8.4 percentage points, represenring a variation of9.8% over the average value ofthe

First Principle efliciency. The equivalent variation for e is 1.14 percentage points,

represenring a variation of21.7 % over the average value ofthe Second Principle efliciency.

The percent variation ofthe Second Principle efliciency is therefore much larger than the

variation in the FU'St Principle efliciency.

Figure 5.3 presents the cost ofspace heating for the oprimization criteria listed in Table 5.10

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in New York, Ontario and Québec. Note that the cost difference between the minimum cost

and the minimum exergy solution is less than halfa cent per kWh, or around [10, 7, 6] % of

the average cost for the four alternatives considered. Note, as we11, that the minimum energy

solution yields, for ail three regions studied, much lùgiler costs ( around [79, 37, 19] % for

New York, Ontario and Québec respectively) than the minimum exergy solution. T1ùs is an

interesting filet indicating since, for this example, that the maximization ofthe resources from

the Ftrst Principle not only is more cost1y but provides the worst Second Principle efficiency,

see Figure 5.2.

nus, the use ofthe Ftrst Principle ofThermodynamics as the sole optimization criterion does

not lead to a rational use ofresources from the perspective ofthe Second Principle wlùch is

viewed as a rational method ofenergy planning but results in the most expensive solution.

The minimization ofboth energy and exergy consumption at the resource level provides an

intermediate cost as weil as a compromise between FIrst and Second Principle efficiencies.

It is important to analyse such intermediate solutions since extreme cases ofmaximum E or

minimum cost may not be achievable in practice.

The question that natural1y follows is how to realise the above-mentioned strategies specially

the one that maximizes the natura1 resources as measured by the exergetic content. The

foUowing subsection discusses alternatives as to how to implement the maYimization of

exergetic efficiency in the space heating model.

The optimization ofthe space heating problem is now considered with weights in the energy

and exergy consumption at the resources level combined with the overall cost at the eustomer

level. This ana1ysis is done te determine the relative weights that must he assigned to cost and

to energy/exergy resources in order to achieve a desired solution (such as the minimum

exergy solution). This weight then indieates te the pIanner how fàr the minimum cost solution

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Table 5.11 Minimum energy/ex.ergy weights (cIkWh) in the linear programming objective toforce the solution to be equal to the minimum "R solution.

Objective Function Dcsircd Québec Ontario NewSolution York

1. Eucrgy and cast (w e"+ct, ) min "0. na. 9.8 18.4

2. Excrgy and cast (w "0. +ct, ) minxa 422 51.3 72.2

3. En andcast w. (e.. + x. )+ ..... min x. 5.7 6.9 9.7na. = not achicvable

is from the desired solution. Some results ofsuch optimiZlltion are presented in Table 5.11.

To interpret the results ofTable 5.11, consider, for example, in row l, that, in New York,

it is necessary to weigh the total energy resources, Ca , by 18.4 c1kWh so that the minimum

solution for the objective fimction w Ca + Co will be equal to the desired solution (m this case

assumed to be the minimum "R solution). This value ofw is very high compared with the

average cost ofthe minimum "R whicb, as shown in Table 5.10, is 5.48 c1kWh. The results

ofall three cases shown in Table 5.11, imply that the minimum cost solution is relatively fàr

from the desired minimum ex.ergy solution and that to achieve the latter one must tax either

the resources, Ca or "R , or subsidize the coS!, Co-

The nex.t section discusses more practica1 ways to induce users to consume energy in patterns

which equal or approximate a given desired solution.

s.s Implementation ofDesired Optimum Solutions

In this thesis, the argument is made that the most ratioDa! way to use naturaI resources is to

•

•

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maximize the overa1l Second Principle efficiency. This argument is made on the basis that

exergy is the appropriate measure ofthe potentiaI usefuIness ofnatura! resources since exergy

constitutes the ability ofenergy to he converted into any other form. Furthermore, as shown

in the previous sections, maximizing the First Principle efficiency alone is not sufficient, in

general, to achieve the best use ofnatural resources.

One way to implement this planning philosophy for system planners is to conceive economie

measures that would make the most efficient solution according to the Second Principle of

Thermodynamics the most economically attractive. Economie measures are strategies that

serve to stimulate society to adopt technologies and energy use patterns compatible with a

given philosophy. Another possible strategy is to increase the public consciousness about the

importance ofexergetie considerations in the planning ofthe utilization ofnatural resources.

The Iatter approach, although no less important, is however not easy to quantifY or analyse

and is not treated any further in this thesis.

In this subsection, a number ofeconomie measures are considered to induce users to conform

to the requirements ofthe minimum exergy solution, assuming that users tend to consume

energy in a manner consistent with minimum cost. The economie measures considered in this

thesis are:

(i) Subsidy in the initial capital cost investment, le;

Cn) Subsidy in the opportunity cost rate, p, at the end-use device level;

Cili) Subsidy ofthe fuel and the electricity tariffs, r;

The subsidies described by the items above modifY the average cost ofthe device over its Iife

time, given by equation 5.9 to ac;", where,


(5.15)[

4(ri - /u-,) :E (1 +sy

(ICI-MC,) (1 + (p-t1p)l' + _IC_I m, /1 + .:...jo..:..1__

• ni !h ni !h Tlic, = -'---.:...-.:...----------:-.....:..-------'-----'/1

The tenns AIC" AI'; and Arj represent the subsidies level in the capital cost, the opportunity

cost rate and in the energy and fuel/rate to the eustomers respectively. Note, in equation 5.15,

that the maintenance costs are not affected by the capital cast subsidy. Note, as weil, that a

given subsidy level in the capital cost will also change the opportunity cost, since the later is

a function ofthe initial capital.

•As noticed in Table 5.8 the difference between the minimum cast and maximum e solutions

in theend-use states (~, i =1 to 4) is the replacement ofsome direct heating by ground-to

air heat-pumps. Therefore, the subsidies considered in this example are applied only to the

ground-to-air heat pump so as to encourage customers to switch from direct heating. An

alternative approach wouId have been to talC direct heating however this was not considered

in this analysis. The minimum subsidy to conform with the minimum exergy is found by

Table 5.12 Minimum % subsidies for varying oPPOrtunity cost rates in the initial capital ofthe heat-pump ground-to-air to induce the minimum exergy and minimum cost solutions tohe identical in Québec.

Opportunity cost rate subsidy0 1 2 3 4("10 pcrycar)

1. Initial Capital Cast Subsidy ("10) 81 78 74 70 66

2. Initial cost average lifc:timc subsidy (dkWh) 3.08 2.97 2.84 2.68 2.50

3. Capital cost and opportunity cost (dkWh) S.s5 4.62 3.82 3.11 2.50

4. Opportunity cost-rate Iifdiwe subsidy (dkWh) 0.00 0.93 1.73 2.44 3.05

S. Total average lifc:timcsubsidy (dkWh) S.sS S.SS S.sS S.SS S.sS.The opportumty cost rate consl(lcrcci W8S 4 %perycar.•

•

•


progressively increasing the subsidies until the minimum cost solution with subsidies is

identical to the minimum exergy solution (note that the minimum exergy solution does not

involve economic considerations).

Tables 5.12 and 5.13 summarize the results oftrials with the various proposed subsidies for

the space heating problem. Table 5.12 shows the subsidies in the initial capital and

opportunity costs for Québec. Severa! points should be highlighted about the results shown

in Table 5.12:

(i) There are various possible combinlltions of initial capital and opportunity costs

subsidies which result in the same exergy solution. For each ofthem the totallifetime

subsidy is 5.55 clkWh.

(u") The initia\ capital cost subsidy in the ground-to-air heat-pump in Québec varies

between SI% and 66% ofthe cost ofthe initial investment for an opportunity cost

rate variation subsidy of0 to 4% per year.

(m") The initia\ cost subsidy over the lifetime ofthe ground-to-air heat-pump varies from

3.0S clkWh to 2.50 clkWh, as the subsidies in the opportunity cost rate increased

from 0 to 4% per year. An increase in the opportunity cost rate from 0 to 4% per year

corresponds to a lifetime subsidy of0 to 3.05 clkWh.

(IV) Note that the opportunity cast rate subsidy in % peryear can be trans1ated ioto clkWh

over the lifetime ofthe device. For example, comparing a subsidy in the opportunity

cost rate of2 with4%peryearimpliesin 1.73 and 3.05 clkWh respectively. Notethat

this correspondence is non linear.

Table 5.13 shows the subsidy in the initia\ capital ofthe heat-pump-ground-to-air and in the

electric rate in order to make the minimum exergy solution equal to the minimum subsidized

cost solution. Analysing Table 5.13 note that:

•

•

•


Table 5.13 Heat-pump ground-to-air initial capital subsidy and maximum rate for theminimum solution XR be the minimum cost solution.

Initial Capital Ratesubsidy

Observations(%) (clkWh) Québccrate (clkWh)

subsidv%

50 3.43 28 4.72

55 3.77 21 5.18

60 4.12 13 5.64

65 4.46 6 6.10

70 4.80 0 6.56No nccd for rate subsidy in Québec(rQB =6.52 clkWh).

75 5.15 0 7.02

80 5.49 0 7.48

85 5.83 0 7.94

90 6.17 0 8.40

95 6.52 0 8.86

Eve:n for 100"10 capital subsidy inNew York100 6.86 0 9.32 (rNY - 16.56 clkWh) and in Ontario (m -

9.56 <:/kWh) somc rate subsidy are required.

(i) Considering row 1, a 50"/0 subsidy in the initia1 capital cost ofthe ground-to-air heat

pump, together with a maximum rate of4.72 c/kWh makes the average Iife-cost of

the heat-pump competitive with direct heating. This implies that a large rate subsidy

in Québec that is 28% ofthe present average rate or 85% for New York. Note that

a subsidy of72% in the electric rate in New York is equivalent to (16.56 - 4.72 =

11.84 c\kWh).

(n) When the initial capital subsidy reaches 70"/0, the maximum rate required is 6.56

•

•

•


clkWh. Since this is approximately equal to the electricity rate in Québec. no rate

subsidy would be required in Québec. On the other band in Ontario and New York

subsidies of (9.56 - 6.56 = 3.00 clkWh) and (16.56 - 6.56 = 10.00 clkWh) are

required respectively.

(JÜ) Even with 100"/0 capital subsidy the maximum electric rate to make the heat-pump

ground-to-air competitive is 9.32 clkWh. Since the electricity tariffin New York and

in Ontario are 16.56 clkWh and 9.56 clkW h respectively, some rate subsidies are still

required even in this case when the heat-pumps are given free ofcharge.

5.6 Closure

This clJapter bas investigated the optimi711tion ofa space heating system subject to constraints

with four diiferent alternatives: electric baseboard, ground-to-air heat-pump, air-to-air heat

pump and direct fossi! fuel heating. The design is based on the minimization ofthe energetic

or ex:ergetic conswnption at the natural resource level and the cost to the eustomer as welI

as combinations ofthese.

Since ex:ergy is the abi1ity ofa given form ofenergy to be converted into any other fonD, it

is argued in this chapter that the most rational manner to optimize any energy system (not just

space heating systems) is byminimizing the exergy consumption at the natural resource level.

In other words, that electric energy systems should be designed by maximizing their 0vera11

ex:ergetic efliciency. The case studied here, showed that although, in some specia1 cases, the

maximum energy efliciency solution may coincide with the maximum ex:ergy efliciency

sohrtion, this is not tIlle in general. Thus, in general, to design energy systems rational1y, it

becomes essenriaJ te explicitly include exergy in the objective iùnction ofthe design problem.

•

•

•

Economie and Exergetie Optimization Analysis of Space He'3ting Systems 119

In order to ensure that the system design corresponds to the minimum exergy solution, it is

hypothesized here that the given energy end-uses will he met by those alternatives that

minimize the cost to the customers. In other words, the end-users of energy will tend to

choose the cheapest alternatives according to their Iifetime costs. Ofcourse, in a real system

there is no guarantee that this hypothesis will he followed exaetly because ofreasons such as

human preferences, convenience, Jack ofinformation or concem for the environment but these

have not been modelled in this thesis.

Thus, diffoent cost inœntives were tested in order for the miniTD1Jm exergy and minimum cost

solutions to he identical. The costs incentives studied were subsidies in the initial capital cost

investment, opportunity cost rate and the energy tariffs. Although the minimum exergy

solution could be achievOO with different combinations of subsidies, those involving ooly

subsidies relatOO to capital investments appear to be easier to implement.

It is notOO that this chapter dealt with the optimal design ofan energy system with ooly one

end-use, namely space heating, thus, the resuIts serve ooly to illustrate the methodology.

Nevertheless, the approach tan he extendOO to more genera\ systems with multiple end-uses

(see following chapter).

•

•

•

Exergetic Optimal Regional Planning

Chapter6.


6.1 Introduction

In tbis chapter, severa! planning scenarios are analysed for two neighbouring energy systems,

name\y the Canadjan provinces ofQuébec and Ontario, each with a diffèrent generation mix

consisting of a combination of natural resources such as hydrauIic potential and nuc1ear

energy (Figure 6.1). The main kinds ofend-uses considered in the energy planning process

areheating, traetionand Jighting, eachofwhichismetbyavariety ofpossible end-use devices

such as: e1ectric baseboard heaters, heat-pumps and motors.

In contrast to the results shown in chapter S, where only one end-use (space heating) was

considered, the present chapter presents an energetic and exergetic analysis for a multiple

end-use case with multiple natural resources. The system is subject to a series ofconstraints

in the available energy and ex:ergy produced by each end-use device as weil as in the

120

• Exergetic Optimal Regional Planning 121

•

~J._I-QlI~llI-.1.c:.),.

--ul1 = ",œ_

n-N-o-......-r-m-s...... -~..--~ ..c__ -1 -""t--.k-{__r

li-< _'1.-"",-),~ "'_ '1.

, ...-I- Il -= +-- -=-oa y

H=,""t-r-t-r- l '"'t.- -~-r-~

io-{- ~

r-< .... .....'- -

~-- --.k-{-r-, ~ ......- ~ 1

11. ...."""- ......

-J __ -.JrtI.-el...~'Ill-.l~ ~

...JIM~I....... 11 = , -_."-l'''~ =:::-le&-...

rr-~,~~ 4-l~ -- . !o-(........""t-r-r_rf-

~K-. ....'l. ..-,....... Il'= = ~-y

H=.""t-r-f-.......~- K-

~--<- li'

--- -----..a--t-----.r- -<--~-

.....~ -..:;- ......-

:..v-u. z:ef1Mry le ••l-etrl.c coot1DQ futUca ga--r. - pont-p1aDt œ - d1nct ....ter bMtbg' 1'llnI.~ D. - _t'Uel.Dt IlOtorTa - uaDepoZ'hiUOD .s.Y1ce a - dKtJ:lc ••t ..:r beat1q DI - iD.u1c1ell:t IIOtœtD - UaDmb.1OD aDd clhtnbat10D 01 - ,.tzole_ aatual naouc. Co • aWc1nt llvll.W;DB ••PAc. beatiDQ fUDaC41 9a • lI&tDJ:al pa n.oarce :u. • 1h:fic1u.t IlOtot'U - alectr1c ba• .t>oa:d co - ~ Datua1 nlloa:c. SB - tpaca bMdJlglta_ • but-pap v~ad·to-a1% aa • IlDCl.u aurgy nlouce es: • coot:1D9Ipaa - but-pap ~o-a1: by - byœo ue:tgy n.oœce WB - _.tu beath;De • d1nct COOUD9 t'unac. 011 • OD.taJ:1o te. - ta_Ua; load

110 - ·':aoa1aa1oD. l1.D.

Figure 6.1 Mede! for regional planning.

intermediate energy conversion stages and in the natura! resources themselves.

A series ofsimulation results is presented inc1uding:

• (i) The 1995 Québec and Ontario system;


•

•

(Ii) The optimization of the 1995 energy systems of both provinces taking into

consideration the F1I'St and the Second Principle ofThermodynamics efficiencies;

(Iii) The influence ofa transmission line connecting both provinces;

(iv) The influence ofstate constraints, that is, inequality lïnùts.

This chapter discusses, as weil, a proposition ofa type oftariffbased on the type-oj-use, as

opposed to the more common time-oj-use tariffs [Ge11ings & Talukdar, 1987; Baldick et al

1992; Me!ero, 1992; Cassanti & Esteves, 1990]. The main motivation for introducing type

oj-use tariffs is to force the system to maximize its overall exergetic efficiency. Simulations

were performed to test different tariffstructures to accomplish this objective.

6.2 Region Characterization and Model Description

The regional planning discussed here relates to the e!ectric energy systems ofthe Canadian

provinces ofQuébec and Ontario. Figure 6.1 shows an elaborate mode! ofthe various types

ofnatura1 resources, refineries, power-plants and end-use devices avai1able in both systems.

Note that hI! e1ectrical interconnection between the two regional systems is also present for

a possible intercbange ofe!ectric energy. For all processes, exergetic efficiency is calcu1ated

assnming the most efficient teebnology avai1able for converting that particular type ofenergy

towork.

FIVe end-usesl were considered,

1 Othcr eDd-uscs such as road llaaspo.ttation could also be considcrcd.


(i) Space heating,

(ri) Cooking,

(Iii) Water heating,

(iv) Lighting,

(v) Traction.

The naturaJ resources considered for this regional planning study were:

(i) Hydra potential,

(ri) Petroleum,

• (Iii) NaturaJ gas,

(iv) Coal,

(v) Nuclear,

which cover the majority ofthe existing naturaJ resources.

Some important charaeteristics ofthe region under study are presented in Table 6.1. Note

that:

(1) The province ofQuébec genaates more tban 96% ofits e1eetricity from hydraeleetric

generatiOD, whereas Ontario generates much less in percent values, that is 29"/0. Since

the avaiIable work: in hydre potential or in e1eetricity is higher than in the other naturaJ

resources considered, it follows that Québec is a reIativeIy "exergetically rich

province" when compared with the province ofOntario.

• (2) Around 80% ofthe beating loaliin Ontario (mainly space heating, cooking and water


Table 6.1 Important supply and load charaeteristics in Québec and Ontario in 1995.

Item Québec Ontario

1. Hydroeleetricity to total eleetric generation ratio (%) 96.1 29.0

2. Direct heating to total heating end-use ratiot (%) 45.4 80.4

3. Eleetric heatinlZ to eleetric load ratio (%) 29.7 18.7.t Space hcating, watcr hcating and cooking.

Sourcc:[Canada, 1993; Québec, 1993; Québec, 1995; Gcrlbard & Li , 1993ab; Law, 1993ab; Zhu& Lodoia, 1993ab]

•heating) is provided by direct oil or gas fumaces or stoves wlùle in Québec this figure

is only 45%. This tends to worsen the Second Principle efficiency in Québec relative

to Ontario.

(3) The eleetric heating load in Québec represents around 29"10 ofthe total eleetric load

while in Ontario this figure is estimated to be around 19"10. Once again, since this end

use is mainly in the form of \'laseboard heaters, the exergetic efficiency in Québec

worsens in comparison with Ontario.

It is important to point out, as we11, that the heating loads in Québec represent around 49"10

of the peak power. In other words, out of 33,270 MW of the peak power requirement

forecasted by Hydro-Québec for 1995, 15,960 MW were foreeasted as total peak operating

demand for resîdential space heating, commercial space heating, hot water for the commercial

sector and dual fuel space heating. The equivalent figure for energy consumed in heat related

loads is 42.8 TWh compared to a total of144.1 TWh (29.7%). This represents a very poor

load fàetor for eleetric heating loads. Thus, any economy in the energy consumed in heating

loads results in appiOximately double the savings in peak power [Québec 1993, 1995].

• Exergetic Optimal Regional Planning

6.2.1 Regional planning mode!

125

•

•

The mode! shown in the Fig<1I"e 6.1 is descnoed by 25 states for each province. Each state is

assumed to he represcnted by two quantities: energy and ex.ergy. The states are listed in Table

6.2. Note that:

(i) The first 12 states represent the energy/exergy end-uses. AlI end-uses are considered

to have two pOSSlole end-use devices, except for the space heating end-use that bas

four alternatives end-use devices;

(ri) The five natural resources, nuclear energy, hydro potential, petroleum, naturaI gas and

coal are represented by the states 13, 14,23,24 and 25 respectively. The naturaI

resources feed either the e!ectric system (power-plants and transmission lines),

represented by the states 18 to 22 or refineries and transportation systems,

represented by the states 15 to 17;

(m) Not all energy conversion devices shown in Figure 6.1 are represented by a state. A

set ofstates that represent a system is10 a certain extent a choice made by the energy

planner. In otherwords, different sets ofstates cao he chosen to represent an energy

system.

(v) The last state shown in Table 6.2, TL, represents the transmission line energy flow

connecting the two provinces;

For each province, a set of12 equationSZ forms part ofthe mode! shown in Figure 6.1. The

first five equations represent the relations between the end-use energy requirements and the

outputs ofthe end-use devices,

2A similar set ofrelatiOllS applies 10 the c:xcrgyvariables.


Table 6.2 States considered for Québec and Ontario.

State Description

1 output ofspace heating furnace

2 output ofbaseboard e1ectric heater

3 output ofheat-pump air-to-air4 output ofheat-pump ground-to-air

5 output ofdirect cooking stove

6 output ofe1ectric cooking range

7 output ofdirect water heating furnace

8 output ofe1ectric water heater

9 output ofefficient motor

10 output ofinefficient motor

11 output ofinefficient Iight

12 output ofefficient Iight

13 nuclear energy resource

14 hydre energy resource

15 output ofoil transportation system

16 output ofnaturaI gas transportation system

17 output ofgas from coaI transportation system

18 output ofoil tired power plant and e1ectricity transmission

19 output ofgas tired power plant and e1ectricity transmission

20 output ofcoal tired power plant and e1ectricity transmission

21 output ofnucIear power plant and e1ectricity transmission

22 output ofbydro power plant and e1ectricity transmission

23 petroleum energy resource

24 naturaI gas resource

25 coal resource

TL transmission line fiow between Ouébec and Ontario,........-. .-The twelve first states COIlcspcmds to the r:=rgy/=gy output ofthe cod use dcvices.

•

•


(6.1)

(6.2)

(6.3)

(6.4)

(6.5)

•where the symbols SH, CI<, WH, TR, LT in equations 6.1 to 6.5 represent the space heating,

the cooking, the water heating, the traction and the Iighting end-uses respectively. Later on

in this chapter an estimation ofthe end-use requirements for Québec and Ontario in 1995 is

presented.

The direct heating end-use states Ct , Cs, ~, must obey,

(6.6)

•

while the total e1ectricity delivered from alI natura1 resources to alI e1ectric end-use devices

requires that,


e2 e3 e4 e6 es-+--+--+-+-+1'JDH 1'JHPga 1'JHPaa 1'JEC 1'JEW

e9 elo en el2 ell-+-+-+-:1:-1'Jat 1'JlM 1'Jzz. 1'JE!. 1'J7I.

128

(6.7)

•

•

Note that in equations 6.6 and 6.7 the parameters 1'JOH, 1'J00 1'Jow, 1'J1IPp> 1'JEC> 1'JEW. 1'JEM. 1'J1M,

1'J1I.> 'lJa and 1'JlL are the FII'St Principle efficiencies ofspace heating fumace, direct cooking

stove, direct water heater fumace, ground-to-air heat-pump, air-to-air heat-pump, e\ectric

cooking device, e\ectric water heater, efficient motor, inefficient motor, inefficient Iighting

device, efficient Iighting device, and the transmission line connecting both provinces,

respective\y. The Iast term in equation 6.7 represents the e\ectric energy to be transmitted to

Ontario from Québec and it is assumed positive for Québec and negative for Ontario.

In equations 6.8 to 6.12 the parameter 1'J represents the First Principle efficiency. The

subscripts 'IR, RE, pp and TI. refer respective\y to the transportation system, refineries,

power-plants and transmission Iines while the subscripts 01, gs, co, nu and hy refer to the

naturaI resources petroleum, naturaI gag, coaI, nuclear energy and hydroelectric potentia1. For

each naturaI resource, it follows from Figure 6.1 that,

el3 =e21

(6.8)1'JPP... 1'J7I....

el4 =e22

(6.9)1'JPPhy 1'J7I.1Iy


(6.10)

(6.11)

•(6.12)

Equations 6.1 to 6.12 define the A matrix and the b vector for the energy system mode!. For

each province one such set ofequations applies. A similar set of 12 equations for each ofthe

two provinces must also be written for the exergy variables with the First Principle efiiciencies

replaced by the Second Principle efiiciencies.

To be able to perform the optùraation simulations for regional plllllllÎng, the end-use

requirements ofeach province must be estimated. This is the subject ofthe next section.

6.2.2 Estimation ofthe end-uses for Québec and Ontario for 1995

As discussed in chapter 3, the end-uses are considered to be the input to the energy system

planning mode! wbile the natural resources and the other states represent the variables to be


optimized. Thus, in order to perfonn optimization studies, it is essential to estirnate the value

ofthe energy and exergy end-uses. In this section, the values ofthe main energy end-uses for

the Canadian provinces ofOntario and Québec are evaluated. The estùnations were based on

statistics from the provincial utilities and Canadian government bodies [Gerlbard & Li

1993ab; Zhu & Lodola, 1993ab, Law, 1993ab, Québec 1993; Québec, 1995; Statistics

Canada, 1994).

The energetic content ofthe end-uses is given by,

(6.13)

•where eu; is the end-use energy ~ c; is the energy supplied to the energy conversion device i

and Th is theFm Principle efficiency (or coefficient-of-perl'onnance) ofthe energy conversion

device i.

Similarly the exergetic content ofthe end-use is given by,

(6.14)

•

where X1Ij is the end-use exergy ~ Xj is the exergy supplied to the conversion device ~ and Ej

is the Second Principle efficiency orthe energy conversior ;evice i.

Notethat the end-uses in bath provinces were el'timated per sector whenever such data were

available. The three sectors considered in this study were:


Table 6.3 End-use energy for Québec in 1995.

Electric Non-Electric TotalEnd-use Sources Sources

GWblvear % GWblyear % GWblvear %

1. Space heating 38,063 52.5 34,467 47.5 72,530 100.0

2. Cooking 643 99.7 2 0.3 645 100.0

3. Water heating 9,234 63.0 5,424 37.0 14,658 100.0

14. Lighting 3,011 100.0 0 0.0 3,011 100.0

S. Traction 51,543 100.0 0 0.0 51,543 100.0. .Source: [Québec, 1993; Québec, 1995 ]

• ti) The residential sector,

(u) The commercial sector,

(Iii) The indnstrial sector.

The majority ofthe available data for the commercial and indnstrial sectors ofOntario and

Québec does not include the efficiency of the energy conversion devices. Thus, here,

whenever these data were not available, it was assumed that each alternative at those two

sectors had the same efficiency as the corresponding alternative in the residential sector.

Tables 6.3 and 6.4 respectively slImmarize the end-use estimates from e\ectric and non

e1ectric sourœs in Québec and Ontario for 1995. In Appendix C, further details are provided

about the e:srimatil)n ofend-uses for each sector and province. Analysing Tables 6.3 and 6.4,

notethat:

(1) The encI-use space bearing requùement is around 20"/0 higher in Ontario than i Québec

but in Québec around 52.5% of me space heating requirements is e\ectric. The


Table 6.4 End-use energy for Ontario in 1995.

132

•

E1ectric Non-E1ectricTotaI

End-use Sources Sources

GWb/vear % GWb/vear % GWb/vear %

1. Space heating 17,865 20.4 69,818 79.6 87,683 100.0

2. Cooking 1,896 58.0 1,375 42.0 3,271 100.0

3. Water heating 5,811 37.8 9,550 62.2 15,361 100.0

4. Lighting 2,634 100.0 0 0.0 2,634 100.0

S. Traction 54.119 100.0 0 0.0 54.119 100.0Source: [Gerlbard & Li, 1993ab; 1995; Low, 1993ab; Zhu & Lodola, 1993ab]

corresponding figure for Ontario is ooly 20.4%;

(2) Due to the Jack ofavailable data, most probably, the estimated difference in the end

use energy for cooking between Québec and Ontario is fairly large. In Ontario, ooly

around 58% ofthe cooking end-use is e1ectric, while in Québec it is aImost 1()()O/O

e1ectric;

(3) The overalI amount ofwater heating requirements for Ontario and for Québec is very

similar, a1though two thirds of the energy to supply that end-use in Ontario have

fossil origin while in Québec the equivalent figure is approximately one third.

(4) The amount ofthe Iighting end-use is estimated to be 14% higher in Québec than in

Ontario. This unexpected estimate results from insuflicient knowledge ofthe Iighting

needs in the industrial sector ofboth provinces;

(5) Fmally the end-use traction in Ontario is evaluated to be approximately 54,119 GWh

in 1995, while the equivalent figure for Québec is 51,543 GWh. In both provinces the

end-use traction in absolute values is second ooly to the end-use space heating.


Table 6.5 Fraction ofthe electric consli'Dption covered by the regional planning study in %.

Ontario

78.1

Québec

88.5

•

•

Table 6.S shows the estimated fractions ofthe total electric load covered by this study, that

is, around 78"/0 and 89% for Québec and Ontario respectively. The types ofloads not covered

by the study are: e1ectrolysis, TV and other miscellaneous types ofloads not specified in the

utilities' forecasts. The miscellaneous loads contain some fraction of the five end-uses

considered in this study (sec Appendix C). The total load is not modelIed becanse the

available data were in some cases classified according to sectors rather than end-uses. For

example, the available data for Ontario's cooking end-uses includes the data for the three

sectors considered, whereas the available data for the cooking end-use for Québec

encompasses only the residential sector. This could explain the apparent inconsistency for the

cooking end-use in Québec and Ontario;

As mentioned earlier in this thesis, the evaluation ofthe end-use requirements is important

since they are the driving force ofthe energy system planning process. Another important

consideration in this process is to determine the limiting cases of the Fl1'St and Second

Principle system efficienciesgiven a set ofpossible system configurations. This is the subject

ofthe next section.

6.2.3 LimitiDg levels ofFPT and SPT efficiencies

In the results that follow, ail possible combinations ofenergy suppliers and end-use devices

are ana1ysed to calculatethe entIgetic and ecergetic efliciencies limiting cases. Tbese limiting


Table 6.6 Cases lirniting the values ofthe First Principle efficiency, Tl.

134

•

Min TI Ma.xTIEnd-use

TI System Configuration TIf System Configurationcol.) ("/0)

thermoelcetric gencration hydroelcetric gencration1. Space heating 31.0 and bascboard e1cetric 223.7 and ground-to-air hcat-

hcatcr pump

2.Cooking 15.8 thermoelcetric gencration 44.6 hydroelcetric generationand e1cetric cooking range and e1cetric cooking range

3. Watr:r heating 26.7 thcnnoelcetric gencration 75.2 hydroeIcetric gencrationand e1cetric water heating and e1cetric water hcating

~. Traction 18.6 thermoelcetric gencration 69.9 hydroeIcetric gcnerationand inefficient moter and efficient moter

5.Lighting 1.9 thermoelcetric gencration 17.5 hydroeIcetric gencrationand inefficient li

.and efficient llRhtin2

t Or ooeffiaent-of-performance

cases deline, for each end-use, the system configuration corresponding to the highest system

Tl or E. Such extreme cases are useful ta establish a range of feasible efficiencies in more

realistic designs. Tables 6.6 and 6.7, respective1y, 5ummarize the cases lirniting the values of

Tl and E for the five end-uses under consideration in the regional planning problem. Analysing

Tables 6.6 and 6.7 note that:

(a) Thermoe1ecttic generation is a1ways part ofthe system configuration for either the

minimum Tl or the minimum E solutions. Thus, thermoe1ecttic generation a1ways bas

the least priority in any optirnizarion procedure;

(b) For every end-use, the minimum Tl and the minimum E solutions are identical. In other

words, the worst design from the FIrst Principle point-of,.view is aIso the worst design

viewed from the Second Principle;

(c) Thebest SPT design aLoo corresponds ta the best FPT design on1y when considering


Table 6.7 Cases limiting the values ofthe Second Principle efliciency, E.

135

•

•

Mine MaxeEnd-use

e System Configuration e System Configuration(0/0) ("/0)

thcrmoel::etric genaation hydroelcetric genaation1. Space hcating 2.1 and bascboard elcetric 6.4 and ground-to-air heat-

hcatcr pump

2. Cooking 4.8 thcrmoelcetric genaation 10.1 direct cooking rangeand elcetric cooking range -3. Walcr hcating 5.3 thcrmoelcetric genaation 8.2 direct water hcating

and elcetric watcr hcating furnacc:

~.Traction 46.5 thcrmoelectric genaation 1 73.6 hydroelectric genaationand incfficient motar and efficient mator

~. Ligbting 0.2 thermoelcetric genaation 2.8 hydroe1cetric g:naatiOl"and incfficient Iilililin2 and efficient lllililin2

space heating, traction or lighting end-uses. Note that in this coDfiguration

hydroelectricity is always part ofthe soL:ion;

(d) The maximum SPT efliciencies for cooking and water heating end-uses occur when

ooly direct heating is used;

(e) Fmally, note th~~ wider range oflimiting values ofT) compared v.ith those ofE. For

example, the case-1imiting values [or tilt: cooking end-use vaIY from 44.6% to 15.8%.

The comparabletigures for the SPT analysisare 10.1% to 4.8%.

It is expected that realistic designs would have their FPT and SPT efliciencies falling within

the ranges as shown in Tables 6.6 and 6.7.


6.3 Regional Planning Optimization Studies

136

•

•

In this section, severa! oprimjzarion studies ofregional planning are presented. The results are

summarize.;l in Table 6.8. Each study is characterized by the following paramett".rs and

variables:

{ï) Transmission line limits;

(Ji) Upper bound limits on system variables;

(üi) Objective function;

(iv) First and Second Principle system efliciencies.

Analysing Table 6.8, the following comments apply to each case study:

(1) The first case study (row one ofTable 6.8) corresponds to the 1995 Québec-Ontario

system. Note that no transmission line or upper bound limits are considered h=. !t

is assumed that no known objective function is optim;zed by the 1995 system.

However, one can argue that the natwal tendency ofany energy system is to approach

the minimum cost solution at the customer level. Note also that the FPT efliciency of

Québec is much higher than the corresponding value for Ontario, 57.7Ofc. versus

34.7%. In contrast, the SPT analysis shows less than three percentage points

difference indieating that according to the SPT perspective, Québec is not much more

eflicient than Ontario. The reasons for this are discussed in Section 6.3.1;

(2) Case study two introduces state variable Iimits and optimizes the F1I'st and the Second

Principle system efliciencies. Again, no transmission line between the two provinces

is considered œthis simulation. Two objective functi:lns are studied: the minimization

ofthe energetic and exergetic resources. For the minimiZllrion ofthe energeric nat;n'a\

resources (Min ~, it is clear ftom Table 6.8 that ail FPT and SPT efliciencies are


Table 6.8 Summary ofcases studied in rcgional planning.

Upper TI 10Case

TransmissionBound Objective ("/0) (%)

SlIIliyUne limit Limil Function10' MW QB ON RE QB ON REl

1 0 b no 57.7 34.7 42.5 30.2 27.7 28.9

Mine" 72.8 41.4 51.8 29.9 32.1 31.02 0 b:

Min"" 55.7 41.4 47.0 36.2 32.1 33.9

Mine" 75.3 57.3 62.2 43.0 34.8 31.33' 10 b

Min"" 60.8 S6.J 55.1 48.7 34.9 34.5

Mine" 76.5 59.8 64.2 43.6 35.3 31.;;4 10 b*U

Min"" 43.6 55.3 31.9 48.1 35.6 35.4

5 JO b lieD 42.7 38.7 405 34.6 315 32.9

6 10 b Ile", & lia" 64.2 56.3 56.7 47.8 34.9 34.1

7 10 b 1110.& lia.: 60.8 S6.J 55.1 48.7 34.9 34.5. ., RE 1$ the rcgJon fClmlCd by the proVIDCCS Québec and OIItario.: The upper bouDd base case 1imits for the provincial states are dcsaibc:d in Table 6.10.• Except bydro resourccs, M1.a•Ô= 1.61.

•lerger than the 1995 case with the exception ofthe SPT efficiency in Québec that is

slightly sma1ler than the 1995 value. The Iast comment applies, as weil for the

minimizarion ofthe exergetic resources, except that, in this case, ail efficiencies are

greater than for the 1995 case. Note that, as expectecl, for minimum exergy, the SPT

efliàency is greater than the corresponding values for the minimum energy solution.

On the other band, for minimum energy, the FPT efliciency is greater than the

corresponding values for the minimum exergy case;

(3) Case study tbree simnJates the ÎIlfiUence ofthe transmission line capacity between the

two neighbouring provinces. The values ofthe FPT and SPT efliciencies shown in

Table 6.8 conespond to a transmission line capacity of10,000 MW. This study case

is further discussed in Section 6.3.3. Note that the value ofthe regional FPT efliciency


•(4)

when the objective function is the minimization ofthe energy resources illcreases from

51.8% to 62.2% because of the acided tie-Iine energy exchange. Note that the

corresponding SPT eflic)ency for the region increases s1ightly from 31.0% to 31.3%,

but the provinces individually had their SPT efliciencies changed by a much greater

proportion. For example, Québec had its SPT efliciency increased by more than 13

percentage points. The reason for this is that a larger ofQuébec's end-use is now in

the form ofelectricity exports to Ontario. In the same manner, the value ofthe system

SPT efliciency when the objective function is the minimization of the exergetic

resources increases from 33.9"/0 to 34.5% with the addition ofthe tie-line between

Québec and Ontario;

Case study four investigates the influence ofincreasing thl' l1pper bound limits in ail

the state variables. The efliciencies shown in Table 6.8 correspond to a relaxation of

10% above the limits considered in the base case (see Section 6.3.5). Comparing the

corresponding values ofcases three and four note that a 10% relaxation in the state

limits increases the FPT efliciencies in ail cases, but not necessarily the SPT

efliciencies. The physical realiZJ!tion of a change in the limits in question is a non

trivial task requiring major investments and a change in the end-uses consumption

patterns;

Study cases S, 6 and 7 correspond to diffèrent experiments carried out to try to acbieve the

minimum exergy solution by the proper choice ofweigbting fàctors in the objective function.

The motivation for these elCperiments was to find a set ofweighting factors corresponding to

energy tariffs wbich, ifintplemented, would induce the end-uses and the utilities to consume

energy in a manner consistent with the minintum exergy solution.

•(5) The first experiment (case study 5) consisted of minimizing an objective function

whose weights were applied ollly ta the end-use devices and were equal to the inverse

of the SPT device efliciencies. This experiment was only partial1y successfil\ in


reaching the minimum solution;

139

•

(6) The second experiment (case study 6) applied the following weights: the output of

every device in the system was weighted by the inverse ofthe SPT efliciency ofthe

device, while every resource was weighted by the inverse of the corresponding II

(fraction ofthe resourœ energy content corresponding to the available work). This

case came closer (Ontario's states, Îor this case, are identical to the minimum ex:ergy

solution) to meet the goal but the weighting factors were somewhat diflicult to

rationalize, since every variable in the system is charged a tariff including the

intennediate and the resource states;

(7) The final ex:periment summarized in Table 6.8 was complete1y successful in achieving

the minimum exergy solution. Fssentia11y, tariffs in the form ofweighting factors were

applied only to the outputs ofthe end-use devices and to the natural resources. The

end-uses output were weighted by the inverse ofthe device SPT efliciencies while the

resources were weighted by the inverse of II. Section 6.3.5 gives more details about

these results.

6.3.1 Québec-Ontario 1995 system

Table 6.8 shows that the Québec-Ontario region in 1995 had FPT and SPT efliciencies of

42.5% and 28.9"/0 respectiveIy. However, from both perspectives, the province ofQuébec is

more efficient than Ontario. On the other band, the SPT efficiency for Québec is not much

cliffe:ent from the corresponding value for Ontario in percentage values. The reason for this

becomes clearby ana1ysing Table 6.9 showing the details ofail the energy and ex:ergy states:

(a) Québec is re1ative1y richer in ex:ergetic resources (hydro) than Ontario bet it uses a

greater proportion for baseboard electric heating among other ex:ergetically inefficient


Table 6.9 Energy and exergy states considered for Québec and Ontario for 1995.

140

•

StateEnergy output in GWh Exergy output in GWh

Québec Ontario Québec Ontario

1 34,466 69,818 931 1,885

2 36,862 16,338 995 441

3 857 1,085 23 29

4 344 423 9 Il

5 2 1,375 0 165

6 43 1,896 77 228

7 5,424 9,550 434 764

8 9,234 5,811 739 465

9 20,872 35,871 20,872 35,871

10 30,668 18,248 30,668 18,248

Il 426 656 51 79

12 1,146 1,977 138 237

13 13,920 192,090 5,568 76,836

14 153,433 41,100 145,761 39,045

15 37,224 55,441 14,890 22,176

16 20,425 61,763 8,170 24,705

17 0 0 0 0

18 1,067 587 1,014 558

19 0 2,114 0 2,009

20 0 24,843 0 23,601

21 4,364 60,220 4,146 57,209

22 134,101 35,921 127,395 34,125

23 50,921 72,608 20,368 29,043

24 26,052 85,454 10,421 34,182

25 0 79,246 0 31,698

TI. 0 0 0 0


uses;

141

•

•

(b) On the other band, although Ontario bas fewer hydro resources, it uses less electric

baseboard heating and more direct heating loads;

(c) The output energyleve1s ofend-uses 1 to 8, (heat-related), 11 and 12, (lighting), are

significantly larger !han the corresponding exergy values. The reason for this is the

relatively low SPT efficiency ofsuch end-uses;

(d) Traction (state~ 9 and 10) bas the same value for energy and exergy;

(e) Considering rows 13, 14,23,24 and 25 (natura! resources nuclear energy, hydro,

petroleum, natura! gas and coal), it is noted that Ontario uses much more fossi! fuel

and nuclear energy !han Québec.

One important issue that arises examining the Québec-Ontario 1995 energy and exergy

scenario is how to improve the use ofthe available natural resources. There is no simple

answer to this question. However, the following approaches are possible:

(i) By optimizing the system at the level ofthe utilities or the customer or bath. This can

be accomplished by systematic programing methods or by ad-hoc r·rograms;

(ü) By broadening the scope of the planning process to include as many end-uses as

possible. For example, ifroad transportation were included in the regional planning

model the overall SPT efficiency could be substantially improved by the replacement

ofinternal combustion engine vehicles (ICEV) by electric vehicles (EV);

(üi) By introducing govemment regulations, tax incentives and special exergy tariffs to

induce bath utilities and customers to adopt solutions consistent with the minimum

exergy plan.


6.3.2 Base case constraints for regional planning

142

The assumed base case upperbound 1imits for the system states are listed in Table 6.10. The

lower bound Iinùts were considered to be ail equal to zero. The upper 1imits were defined as

afunction ofthe 1995 values. For example, states 1and 2, the outputs ofthe space heating

fumace and electric baseboard heater, respectively, were aIlowed to vary from zero to 100010

ofthe maximum ofthe 1995 values ofel a.'1d ~. Then,

(6.15)

•

•

where U1,2 is the upper bound limi'"..s Ïcr states 1and 2.

In choosing the upper bound 1imits of the system states, a certain amount of subjective

judgment was used. The rationale for the choices made in Table 6.10 is described be1ow:

(i) Heating fumaces and electric baseboards (states 1 and 2) have more flexible 1imits

than the her~-pump options (states 3 and 4) to reflect the substantially greater life

costs ofheat-pwnps. ln oth<:r words, the cost1ier the device, the lower the assumed

upper bound 1imit;

(u) Direct heating devices were estimated to have a 1imit 100010 above the corresponding

electric end-use device options. This reflects the fact that the direct heating options

are most like1y to be adopted by the QlStomers in the advent oftype-of-use tariffs due

to their relatively high SPT efficiencies and low cost;

(ili) Nuclear energy resources in both provinces were estimated to remain at their 1995

levels as a result ofenvironmental restrictions;

(IV) The upper limits on the hydroelectric resources in Québec and in Ontario were

estimated to be, respectively, up to 100% and 10010 above the 1995 levels. This


Table 6.10 Upper bound (base case) state limits considered for regional planning.

143

•

•

Québec Ontario ObservationsStatc

GWh GWh Limits above 1995 values

el 73,724 139,636 100"10 ofthe maximum value ofthe el and C:! states oft1:le

C:! 73,724 139,636 lespcx:ti.e province

Cs 1,071 1,356 ~%m~maximumval~m~Cs~~statesm~

e, 1,071 1,356 respective province.

e:, 1,286 3,792 100"10 of the maximum value ofthe e:, and Co states ofthe

Co 1,286 3,792 respective province.

e, 18,468 19,100 100% ofthe maximum val~ of~ e,~ Cs states ofthe

Cs 18,468 19,100 lespcx:tive province.

Cs> 38,335 44Jt~:I ~% ofthe ."QllXÎmum val~ of~ Cs> and c,o states ofthe

elo 38,335 44,839 lespcx:tive pn'vince.

C,I 1,433 2,471 ~%of~maximum val~ ofthe C,I and c,: statesof~

c,: 1,433 2,471 respective province.

e" 13,920 192,0900%of~maximum val~ of~ c" state ofrespective~province.

c" 306,866 45,210 100% and 10"10of~ maximumval~ of~ c" state of~ respecti»e province.

c's 372,245 617,631 900%of~maximum valueof~ c's~ C,6 states of

C,6 372,245 617,631 ~ respective province.

c" 0 0 0"10of~maximum value.,r~ c" state mrespective~province.

c,. 268,201 120,441

c,. 268,201 120,441

C:!o 268,201 120,441 l00"loof~ maximum valueof~ c,. te C:!: statesof~respective province.

C:!I 268,201 120,441

C:!: 268,201 120,441

e:. 509,208 854,538 900%of~ llJ8YÏmnm valueof~ e:.~ e.. states of

C:!, 509,208 854,538 the respective province.

C:!s 0 854,5380% and 900%of~maximum valueof~ C:!s statem~.


reflects the considerably higher hydroelectric potential in Québec;

144

•

(v) The output ofnaturaI gas and oil transportation systems as weil as the output ofaIl

types ofelectric transnûssion Iines and power plants were aIIowed to vary up to 900"/0

of their 1995 values. This was done sa !hat the results of the oj.ltimization not be

constrained by these intermediate states. In other words, it was decided to restrict the

optimal design by 1imits on the naturaI resources and end-use devices only.

6.3.3 Impact of transmission line capacity

This section presents the results ofsimulatîng increasing transmission line 1imits between the

neighbouring provinces ofQuébec and Ontario. The intent is to try to improve the regional

efliciency by increasing cooperation. Two sets ofsimulations were done, the maximization

ofthe SPT (Table 6.11) and FPT (Table 6.12) efliciencies. In bath cases, the transmission line

1imit'~ varied in increments of 1,000 "MW up to a point where further increases did not

affect the optimum system efliciency. When considering the interchange ofenergy between

the two neighbouring provinces, the electric energy received by Ontario from Qu~ is

considered as a Québec end-use. On the other band, the electric energy received by Ontario

from Québec is treated as a resource for Ontario. These definitions are used to find the

provincial efliciencies in an interconnected system.

For example, from Table 6.11 it can be seen that, by adding a 10,000 MW transmission line

3 Note that sincc the Iinccapacity is in MW, in orcier ta fiDd ils yearIy c:ucrgy tnmsmission, a

load factor of60"/0 was assumed.


•

•

Table 6.1 1 SPT efficiency, for max e, for increasing values oftransmission line capacity.

Transmission line dataObjective Funetionfrom Québec to Ontario

MaxeCapacity Optimum Flow1()lMW 1()lMW Ouébec Ontario R.eltion

0 0 36.2 32.1 33.9

1 1 38.0 32.3 34.0

2 2 39.6 32.6 34.1

3 3 41.2 32.9 34.1

4 4 42.6 33.3 34.2

5 5 43.9 33.6 34.3

6 6 45.2 33.9 34.3

7 7 46.4 34.2 34.4

8 8 47.5 34.5 34.4

9 9 48.5 34.9 34.5

10 9.2 48.7 34.9 34.5

II 9.2 48.7 34.9 34.5

one can improvethe optimum SPT efficiency ofthe system from the 1995 level of33.9"/o to

34.5%. Above a line capacity ofl1,OOO MW, the maximum SPT efficiencies ofthe provinces

and oft~ system are not aflècted. Thus, it does not pay to increase the line capacity beyond

11,000 MW for the purpose offurther increasing the optimum SPT efficiencies.

Note aIso, from Table 6.11, that the optimum SPT efficiency in Québec increases with higher

transmission f1ows. This is reasonable since a greater proportion of Québec's end-use is

devoted to supply Ontario with dectric energy, that is, an end-use with a high exergetic

content. From the same table it cao be seen that Ontario's optimal SPT grows, a1beit at a

lower rate. This behaviour is due to (t displacement ofless efficient thennoelectric sources


•

•

Table 6.12 SPT efficiency, for max T'J, for increasing values oftransrnission line capacity.

Transmission line dataObjective Function

frOID Québec to OntarioMaxT'J

Capacity Optimum Flow1Q3MW 1Q3MW Québec Ontario R on

0 0 29.9 32.1 31.0

1 1 31.6 32.3 31.0

2 2 33.1 32.6 31.1

3 3 34.6 32.9 31.1

4 4 36.0 33.3 31.2

5 5 37.4 33.6 31.2

6 6 38.6 33.9 31.2

7 7 39.8 34.2 31.3

8 li 40.9 34.5 31.3

9 9 42.0 34.9 31.4

10 10 43.0 34.8 31.3

11 11 43.9 34.7 31.2

12 12 44.9 34.6 31.1

13 13 45.7 34.4 30.9

14 14 46.6 34.2 30.7

15 15 47.4 33.9 30.5

16 16 48.1 33.7 30.3

17 17 48.9 33.4 30.1

18 18 49.6 33.2 30.0

19 18.1 49.8 33.1 30.0

20 18.1 49.8 33.1 30.0

by imported hydroelectricity. The system efficiency saturates al 34.5% due to the IDOst


•

•

35 - . . . · · · · · " · · · · · · · · · · · . · · . . . · . · · - - - · · · · · · - - - · - "

Min XR

34- -.-. · · · · - - , · · · . · · - - - · · " · · . · . · 0 - - -, - 0 - 0 · 0 0 0 · 0 · · ·.....

-!~33- 0 0 . · · · · · · . . · 0 · - · · · 0 0 0 0 - 0 0 · - - 0 - - · · . · . · 0 · 0 · 0 0 0 0 · · 0

0,

c..'0E...... ·l1.<0.32- 0 . 0 - · · · · - 0 · 0' · · · 0 · 0 - · · · • '0 · · 0 0 0 · 0 · 0 0 · .' . . · · · · · . · · · · ·c.5! :Min

~Q.. ·Œ - "'"..;,. - ·- ......... "'"31 · · . · · . . · · · . · · · · · · · ·.. · · -.,· · . · . · . · · · · · . · · · · '., ·

"·

. '- ·.30 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

0 5 10 15 2Transmission line capacity (1000 MW)

Figure 6.2 Second Principle efficiencies for increasing values oftransmission line 1imits.

efficient end-uses devices such as heat-pumps reaching their upper bounds (see Section

6.3.4).

Asecond set ofsimulations was aIso carrled out where the F11"St Principle system efficiency

was maximized (Table 6.12). Note that for this set ofsimulations the Québec's optimal SPT

efficiency increases from 29.9"/0 to 49.8%, again mainly because ofthe higher electricity

exports treated as end-uses. It is noted that the SPT efficiency under the conditions of

maximum FPT is, as expected, a1ways below the corresponding value when the objective is

to maximize the SPT system efficiency. It is interesting to note, however, (see Figure 6.2)


•

•

that, under maximum FPT efficiency, the maximum line capacity beyond which the solution

does not change occurs at 19,000 MW ( compare Tables 6.11 and 6.12).

However, from Figure 6.2, it can be noted that the SPT efliciency actually worsens beyond

a line capacity of 10,000 MW under the minimum energy solution. This is due to the

rep\aœment ofsome direct heating in Ontario by baseboard e1ectric heating after heat-pumps

reach their leve1 ofsaturation.

6.3.4 Comparison of the 1995 case with the maximum SPT system

efliciency solution

This section descn"bes and compares in detail the 1995 case and the minimum xRbase case

(Table 6.8, case 3). These data are important to p1anners since they detail the exact changes

to the 1995 system to achieve a desired optimum solution.

Tables 6.13 and 6.14 respectïve1y represent for Québec an<LOntario the values ofthe states

for the 1995 case, the minimum "R solutionas weil as the upper bound IimiU. Analysing these

tables, the maximum SPT efficiency solution requires that the following changes be applied

to the 1995 case:

(i) Heat-pumps (3, 4), efficient motors (9) and efficient Iighting (12) must be set to their

maximum Iimits in both provinces;

(n) On the other band, deetric baseboard (2), e1ectric cooking range (6) or e1ectric water

heating (8) must be e1iminated from the optimum solution for both Québec and

Ontario;

(m) The GWh output of direct space heating fumaces (1) must be equal to the

•

•

•


Table 6.13 Comparison of 1995 and Min XR solutions in Québec.

Energy States e.. k=1•...25

State 1995 case MinxR UpperboundGWhJvear GWhJvear GWhJYe:JI

1 34.466 70.387 ï3.724

2 36.862 0 73.724

3 857 1.071 1.071

4 344 1.071 1.071

5 2 645 1.286

6 643 0 1.286

7 5.424 J4.658 13.468

8 9.234 0 18.468

9 20.872 38.335 38.335

10 3''1,668 13.205 38.335

11 426 140 1,433

12 1,146 1,433 1,433

13 13,920 0 13,920

14 153,433 150,333 306,866

15 37,224 63,054 372,245

16 20,425 63,054 372,245

17 0 0 0

18 1,067 0 268,201

19 0 0 268,201

20 0 0 268,201

21 4,364 0 268,201

22 134,101 131,391 268,201

23 50,921 80,426 509,208

24 26,052 80,426 509,20'3

25 0 0 0

149


Table 6.14 Comparison of 1995 and Min xR solu~ons, in Ontario.

ISO

•

•

Energy states e., k=1,...25

State 1995 case MinxR UpperboundGWhlvear GWhlvear GWhlvear

1 69,818 84,952 139,636

2 16,338 0 139,636

3 1,085 1,356 1,356

4 423 1,356 1,356

5 1,375 3,271 3,792

6 1,896 0 3,792

7 9,550 15,361 19,100

8 5,811 0 1~,100

9 35,871 44,839 44,839

10 18,248 9,280 44,839

11 656 162 2,471

12 1,9n 2,471 2,471

13 192,090 0 192,090

14 41,100 45,210 45,210

15 55,441 76,760 617,631

16 61,763 76,760 617,631

17 0 0 0

18 587 0 120,441

19 2,114 0 120,441

20 24,843 0 120,441

21 60,220 0 120,441

22 35,921 39,513 120,441

23 72,608 97,908 854,538

24 85,454 97,908 854,538

25 79,246 0 854,538


•

difference between the space heating requirement and the amount supplied by heat

pumps (3, 4). Thus, the output ofdirect space heating furnaces (1) must morethan

double in Québec while, in Ontario, it had to increase by more than 20"/0 compared

to the 1995 case;

(iv) Inefficient Iighting (11) must be used only when efficient lighting (12) bas been

saturated;

(v). No natural resource or intermediate conversion device reached its Iimits, ex:cept hydro

resources (14) in Ontario;

(vi) Nuclear energy (13) must decrease to zero in spite ofthe fàct that, nuclear energy

represents a major energy supplier in Ontario in 1995;

(vii) Hydro e1ectricity (14) decreases by 3,100 GWh in Québec. Using a 10ad factor of

60% this corresponds to approximately 600 MW reduetion in hydroelectric

generation! This is a surprising but a beneficial result that is even though e1ectricity

ex:ports increase, the overa1l e1ectricity generation decreases;

(viii) Th:: ;~ve is due to a substantial increase in the amount ofoil (23) and natural gas

(24) resources consumed. For ex:ample in Québec oil (23) must increase to

approximately 50,000 GWh to 80,000 GWh, while natural gas (24) increases from

approximately 26,000 GWh to 80,000 GWh;

(IX) The use ofcoal in Québec remains at the zero Ievel while in Ontario it drops to zero;

(x) No thermoe1ectricity is required in either ofthe provinces. Thus, the only oil-fired

plant in Québec would have to he shut down. On the other band, in Ontario, al1 ofits

1995 thermoe1ectricity, that is 87,765 GW"IJ, would have to he rephced by

hydroelectricity generated by either Ontario itseIfor by Québec.

(Xl) The overall energetic resources decreases from the 1995 value of715 TWh to 552


•

TWh, in the minimum exergy solution. This is a reduction of approxirnately 23%

wlùch corresponds to approximately 10,000 MW ofthermoelectric generation.

Another important aspect :0 consider in the planning ofenergy systems is the sensitivity of

the optimum with respect to the upper bound state linüts. The next section discusses tlùs

topic.

6.3.5 Upper bound Iimits relaxation

In order to have a better understanding ofthe influence ofupper bound state limits on the

system behaviour, t1JA sensitivity ofthe objective function with respect to each state variable

limit was calculated. In tlùs section, such sensitivities are analysed fer both the base case

upper bounds described in Section 6.3.2 and for a modified base case. For the modified case,

an end-use devices and hydro resources were limited by a value 100/0 above t..if~ 1995 levels.

The 0Jébec-Ontario transmission line was limited to 1,000 MW, while an other stat~ limits

rernained unchanged. The upper bounds ofthe modified base case are much more restrictive

than in the bp.se case (see Table 6.10). Tois was done on purpose to check the influence of

the upper bound limits on the system exergetic behaviour.

The sensitivity ofthe objective function with respect to an active upper bound limit is given

by the corresponding Lagrange multiplier found during the optimization process. A selected

number ofsuch Lagrange multipliers for both the base case and the modified base case are

shown in Table 6.15. Note that:

•(i) The Lagrange multipliers ofthe direct heating end-use device options are nulI in the

~ case since their limits were not reached either in Québec or in Ontario;


Table 6.15 Lagrange multipliers for selected states for minimum exergy.

Lagrange multiplier

State' Basecasc% ModificdBaseCaser

Québec Ontario Ontario Québec

1 Output ofspace heating fumacc 0 0 1.44 2.09

3 Output ofground-to-air bcat-pmnp 022 0.10 1.66 1.93

4 Output ofair-to-air hcat-pllIllp 1.02 0.93 2.45 2.85

5 Outputofdirect cooking steve 0 0 0.79 1.07

7 Output ofdirect water heating fumace 0 0 0.35 0.61

9 Output ofefficient-moter 0.05 0.05 0.05 0.05

12 Output ofc:(!iciCllt lighting 10.57 11.12 10.57 1228

14 H~resource 0 0.01 0 0.02

Transmission line flow bctwœnTL

Québec and Ontario 0 0.01

..• The states' dclinibOll1istlSfoundm Table 6.3.1The upper bouDd limils base case arc dcfiDcd in Table 6.11.1AIl Clld'IISCS dcviccs and hydro resourccs in bath provinces limited to 10% bcyond of1995 values,tnmsmissiOllIinc Québcc-OnIario limill,OOO MW, the=iDing states limited as base case.

•

(ü) In both provinces, efficient lighting bas the highest Lagrange multiplier. This implies

that a small increase in the UP!'ef bound of efficient lighting (12) wiIIlead to the

Iargest improvement in the system SPT efficiency when compared to increasing the

limits ofother states which are saturated. This filet is observed in both the base and

the modified base cases;

(üi) It is interesting to note that the sensitivity ofthe efficient motor with respect to ils

Iimit is the 10wesl among the states with non-zero Lagrange multipliers. This suggests

• somewhat paradoxic:illy that increasing the maximnm Iimit on efficient motoIS ,'IÏll


•

have the least effect on the overall SPT efficiency, when compared to, for example,

the ground-to-air heat-pump. However, tIis res. 'lt is not illogical since both efficient

and inefficient motors have relative1y high and similar efficiencies;

(iv) The sensitivity ofthe optimal SPT efficiency with respect to the transmission flow

limit is very low indicating that, to the extent possible, it is preferable to increase the

limits of exergetically efficient end-uses devices than to increase the limits on the

transmission floW;

(v) According to Table 6.15 the prefeued order ofmodification ofthe upper bound levels

is as defined by the increasing order ofmagnitude ofthe Lagrange multipliers.

(iv) The sensitivity of hydro resources in Ontario is non zero, as opposed to the

corresponding value in Québec, indicating that these resources have reached their

assumed upper bound limits in Ontario but not in Québec.

Another important step to consider in energy planning is the implementation ofmeasures that

will induce the system to behave in a manner close to the min Xa solution. This is the subject

ofthe next section.

6.3.6 Exergetic or type-of-use tariffs

The rea'ization ofactions that leads te more exergetically efficient systems is discussed in this

section. Among the possible alternatives to achie-.i: a system that consumes its natura\

resources more efficiently according to the Second Principle ofThermodynamics one find:

talc incen~ programs, public awareness and the introduction of tariffs that reflect


Table 6.16 Objective function for ext"I"8etic tariffdesign.

Objective fimction

Statc (i) (ü) (ili) (iv)lIe~ lie,. lIe~& lI(X"t Minx~

1 20.3 20.3 20.3 0.0

2 352 352 35.2 0.0

3 20.7 20.7 20.7 0.0-

4 13.7 13.7 13.7 0.0

5 7.8 7.8 7.8 0.0

6 15.s 15.5 15.5 0.0

7 9.6 9.6 9.6 0.0

8 13.8 13.8 13.8 0.0

9 12 12 12 0.0

10 1.6 1.6 1.6 0.0

11 131.9 131.9 131.9 0.0

12 39.6 39.6 39.6 0.0

13 0.0 2.5 0.0 1.0

14 0.0 1.1 1.7 1.0

15 0.0 1.0 0.0 0.0

16 0.0 1.0 0.0 0.0

17 0.0 1.0 0.0 0.0

18 0.0 1.1 0.0 0.0

19 0.0 1.0 0.0 0.0

20 0.0 1.1 0.0 0.0

21 0.0 1.1 0.0 0.0

22 0.0 1.1 0.0 0.0

23 0.0 2.5 2.5 1.0

24 0.0 2.5 2.5 1.0

25 0.0 2.5 2.5 1.0

51 0.0 l.l 0.0 0.0. .TAlI the œsoun:es have a wetgbting factor of lia. c:xœpt the hydro rcsoun:c that bas a factor of(1/a.)·1l, wb= Il was expcrimcntally fOUDd to bc cqual to 1.61.•

•


the rationale ofthe SPT.

156

•

•

This section discusses ways to implement the maximum regional ex·.'igetic efliciency solution

through the concept oftype-of-use tariffs. This concept will charge CO:lSUIllers different rates

depending on the exergetic efliciencies ofthe end-use device. Such a tariffis analogous to the

more common tîme-of-use tariffs already existing. However, type-of-use tariffs would have

the tendency to induce consumers to use exergy more efliciently, thereby forcî."1g the system

doser te the minimum exergy solution. Thus, it is assumed that both utilities and end-users

will push the system to a minimum exergy solution in an attempt to minimize their cost.

Three possible objective functions were tested to simulate the concept of a type-of-use tariff

(see Table 6.16) where the objective function, t; is ofthe fonn,

(6.16)

The weigbting coefficients, wt , in the objective function represent' the type-of-llse tariffs. The

following types ofweighting coefficients were studied:

(i) The inverse ofthe SPT efliciency for ail the end-use conversion devices, lIE~

(ù) The inverse ofthe SPT efliciency at the end·use conversion devices, liED> combined

with the inverse ofthe estimated available exergy in the naturaI resources, 1/a.a.';

(Ù!) The inverse ofthe SPT efliciency, 1/EoIIo for each conversion device;

• The relative magoitudes ofthe weigbting factors are proportional 10 the tariffs.

5 In tbis case an the natural resoun:es have a weigbting factor of 1/0:", with the c:xccption of

the hydroe1cctricresoun:cwbc:re it is given by 1.6Uaa,...


Table 6.17 Surnmary ofcases studied in regional planning.

Tl EObjective (%) (%)Function

QB ON RE QB ON RE"

(i) liED 42.7 38.7 40.5 34.6 31.5 32.9

(ri) lIEolI & lIexa 64.2 56.3 56.7 47.8 34.9 34.1

(w) liED & lIexa· 60.8 56.3 55.1 48.7 34.9 34.5

(iv) Min"R 1 60.8 1 56.3 1 55.1 1 48.7 34.9 34.5., RE 15 the rcgJon formcd by the proVInces Québec and Ontario.

t The upper bound base case limits for the provincial states are dcscribcd in Table 6.10.• Exccpt bydro rcsourccs, ô/a.... ô =1.61.

(iv) The coefficients for the minimUffi ; solution are also shawn in column 4 for

comparison.•

Table 6.16 shows, for each type, the corresponding weighting factors ofthe states in bath

provinces. Analysing Table 6.16, please note that:

(i) The assumed weighting factors for the first 12 states are the same for the first three

objective functions tested. The twe1ve first states correspond ta the end-use devices,

as defined in Table 6.2;

•

(ri) Among the end-uses, tr..crlon with an efficient motor bas the sma11er weighting factor,

1.2, whi1e inefficient lightiog the highest one 131.9. That is, the ~-of-use tariif for

inefficient lighting is the highest while, that ofthe efficient motor is the lowest;

(w) In the minimum exergy solution, column four, a1l natural resources (13, 14,23,24,

25) are weighted equally.


•

•

(iv) For the type (m), object.ve function note that aIl the end-uses devices have higher

weighting fuctors than the natuIë'1 resources, with the exception ofthe traction re1ated

end-uses (states, 9, 10). This indicates that the end-use devices should he charged

relatively more than the natura1 resources. The pœfelled tarifffor the traction end-use

makes sense within the context of the exergetic tariffs since the traction end-use is

100% exergy ~nd sk-::uid then he rewarded.

Table 6.17 summarizes the FPT and SPT efficiencies for the three types oftariffs as weil as

the minimum "R optimal solution. As shown previously in Table 6.8 the objective function (m)

above, produces the identical resu1ts as the minimization of the exergetic resources. This

indieates that the optimal solution achieved by minimizing the exergetic consumption at the

natura1 resources leve1 could be achieved by assigning tariffs proportional to the weights for

eacb ofthe end-use devices and naturaI resources.

0.4 Condudîng Remarks

This chapter had presented a series of simulation resu1ts on the optimum planning of a

regional energy system composed ofthe Canadian provinces ofQuébec and Ontario. The

system had been redesigned by minimizing ofthe total energetic or exergetic consumption at

the naturaI resources leve!. These optimum designs are then compared with eacb other and

with the existing 1995 system.

Mede! for regional planning

The general en~/exergy mode1 described in previous chapters was applied to this regional

planning study. This study encompasses five types of naturaI resources ( hydre, nuclear,

petroleum, naturaI gas and coal) and five types ofend-uses ( space heating, cooking, water


•

•

heating, traction and lighting). In addition, the most common end-use devices such as: power

plants, refineries, efficient motors, heat-pumps, Iighting were considered by this mode!.

Estimation ofend-uses

An estimation of realistic model parameters, in particular the provincial end-uses was

perfonned. A1though this estimation is approximate, it is based on observed end-use patterns,

on published data and is representative ofthe rea1 system.

Estimation ofstate upper bound stlIt<:s' limits

An estimation ofthe Iimits for each ofthe states was performed. This estimation was based

on the variations ofthe assumed 1995 values.

Optimization studies

A series ofoptimal regional planning studies was performed. Two main objective functions

were used, that is, the minimization ofthe energetic and the exergetic resources at the system

1eveI. The importance ofexexgetic optimiZlltion is emphasized throughout the chapter. It was

demonstrated that the optimization performed on the basis ofthe First Principle aIone does

not usua11y maYimize the exergetic resources in a multiple end-use and naturaI resources

constrained case.

Exergy conservation

It was argued that the exergy conservation is, in general, more important than the energy

conservation, since exergy is the measure ofthe avai1able work, in a given process or source

ofenergy. Exergy encompasses a measure ofquality of .le energy use, and should al least

he regarded equa1ly together with energy in regional planning.

Influence ofQuébec-Ontario transmissio~ line capacity

The influence ofincreasing the capacity of the transmission line connecting the two provinces


•

•

was tested. It is shown that the ideal transmission line capacity is different (almost double)

if the objective funetion for optimization purposes is changed from minimum exergy to

minimum energy consumption at the resource leve1. Thus, the minimum exergy solution

requires a lower investment in transmission lines.

Major differences between minimum e:s.ergy and 1995 cases

The adoption of a minimum exergy solution was compared to the 1995 energy/exergy

consumption leveis. It was noted that all available exergetically efficient end-use devices were

pan ofthe optimal solution. This implies a switch to direct heating fumaces, efficient motors

and Iighting to supply the end-use demand. On the other hand, options such e\ectric baseboard

and, eleetric water heating were not chosen by the optimization procedure. It is also

interesting to note that no nuclear, oil, coal or natura! gas power-plants were necessary for

both provinces in the minimum exergy case. It was shown that the adoption of the

minimization of the exergetic resources will save approximate\y 23% of the 1995 energy

consumption or ncarly 10,000 MW ofthermoelectric generation.

Realiz&bility of minimum e:s.ergy solution

The results ofoptimizing the system by minimizing the exergy al the natura\ resource level

should he seen as a long term goal rather than a plan ofaction to be implemented in the short

tenD. Some ofthe changes stipuIated by the minimum exergy solution such as the shut down

ofnuclear power plants and thermoelectric systems involve additional economic, politica\ and

social considerations outside the scope ofthis thesis.

Sensitivity analysis

A sensitivity ana1ysis was perlbrmed by the examinarion ofthe Lagtange multipliers ca\culate.l

in the optimization process. This ana\ysis allows the energy planner to rank the relative

incrernenta1 impact ofincreasing the hmits ofthe outputs ofthe various end-use devices in the

overa\l SPT or FPT efficiencies. The sensitivity ana\ysis showed that the relaxation on the


•

•

end-use device limits is incrementally, a more efficient measure than the relaxation of the

hydro resourees in Ontario or the increase in the transmission line limit connecting Québec

te Ontario. However, it is known that the relaxation on some ofthe upper bounds limits is not

a simple task when compared to the increase ofthe ù"3llSIlÙssion line levels connecting the

two neighbouring systems.

Type-of-use tariffs

It is demonstrated that it is possible to achieve the minimum exergy solution by the proper

choice of the weighting factors in the objective function. The weighting factors are

proportional to the inverse ofthe Second Principle efficiency for end-use deviees and to the

inverse ofthe fraction ofavaiIable work (exergy) for natura1 resources. The weighting factors

are rationaIized as type-of-use tariffs. It is believed that type-of-use tariffs might be

implemented in steps starting, for example, with only two or three categories such as heat

re1ated and non heat related loads. As metering technologies and other regu1ation constraints

permit, other type-of-use categories could be implemented. This is anaIogous to migrating

!Tom time-of-use, with only two periods to hourly spot priees. The main motivation for

introducing a type-of-use tariff is to force the system to maximize its overaII exergetic

efficiency.

Implications of type-of-use tarilTs in the economic sectors

The impact ofthe ad~ption oftype-of-use tariffs in the diffèrent economic sectors will resuIt

in an overaII smaIIer tariffburden to those sectors already using traction as a major end-use.

This is the case in the industrial sector as opposed to residentiaI and commercial sectors.

Changïng the planning scope

It is important to point out that the overaII SPT efficiency could be substailtially increased by

other means than the ones mentioned above. This would be possible, for example, ifother

types ofend-uses such as the end-use road transportation could be suppIied massiveIy by

• Ex-.=rgetic Optimal Regional Planning 162

•

•

e1ectric traction. Ifthis were done ",ithout changing substantially the generation limits, then

part of the end-uses devices must change to more exergetically efficient alternatives and at

the same rime re1ease sorne electric power.

•

•

•

Conclusions and Recommendations for Future Research

Chapter 7. Conclusions and

Recommendations for Future Research

7.1 General Conclusion

This thesis bas presented a system apprcaeh fOi" the planning of e1ectric energy systems

inc\uding a new peispedÏVe, name1y, the consideration of system efficiency as measured not

only by the more commonly used FIISt Principle ofThermodynamics but, aIso, by the Second

Principle ofThermodynamics. It is shown that the extension ofthe efficiency criterion to

include the Second Principle would result in important changes in the way e1ectric energy

systems are designed and operated.

7:J. Specitic Conclusions

This thesis bas extended the knowledge of planning ofe1ectric enp.!"gy systems through the

following contributions:

163

• Conclusions and Recommer.dations for Future Research

(1) Exergetie ana1ysis in the eontext oflntegrated Resource Planning;

164

•

•

(2) Development ofan energetie and exergetie general model for the design and ana1ysis

ofelectrie energy systems;

(3) Demonstration ofthe impact ofexergetie considerations on the planning process of

electrie energy systems;

(4) Integration ofenergetie, exergetie and economie ana1ysis;

(5) Energetie and exergetie regional optimization study;

(6) A proposition of a new kind of electrie rate, type-oj-use tariffs, that incorporate

exergetie considerations.

The specifie conclusions are now det3i1ed reported in the same order as above.

7.2.1 Exergetic anaIysis in the context ofIntegrated Resource Planning.

Exergetie analysis is extremely helpful to achieve one of the most diflicult objectives of

Integmted Resource Planning whieh is the rational matching ofresources and end-uses. The

term end-use does not describe the kWh consumed by a load but, rather, its useful output or

its service. The rational matching of resources and end-uses is possible becanse one can

interpret exergetie efliciency as a measure ofthe quality ofuse ofa given naturaI resource.

Exergetie analysis then, provides the energy p1anner with a very important perspective that

incorporates bath energy use and quaIity ofthis use in a quantitative way. This thesis argues

that exergy coDSelVlltion is, in general, more important than energy conservation :iÎDce exergy

measures avaiIable work in a given process or source ofenergy. Thus, in general, te perform

the planning ofenergy sYstems rationally, it becomes essential to explicitly include exergy in

• Conclusions and Recommendations for Future Research 165

•

•

the objective function ofa design problem. At least exergy shou1d be regarded on an equal

footing with energy in the lntegrated Resource Planning process.

7..2.2 Development ofan energetic and exergetic general model for the

design and analysis of electric energy systems.

A model was developed to descnoe the general energetic and exergetic interconnection

relationships among the three main constituent parts of an electric energy system (natura!

resources, energy conversion processes and end-uses). The model pennits the classification

ofthe mains system parts into classes. For example, one Sl!ch class is composed ofthe various

types of space heating devices (e.g., baseboard, heat-pump air-to-air, central oil-fired

fumace). The end-uses, considered the independent variables of the model, cao also be

classified by sectors (residential, commercial, industrial or institutional).

The principal advantages ofthis model are to:

(a) Provide flexibility to study and design a broad spectrum of electric energy system

scenarios ofvarying size and complexity. This fie:xibiIity was provided through a user

ftiendly software environment;

(b) Simulate system planning scenarios based on different perspectives such as: energy,

exergy, cost or combinations ofthese;

(c) Optimize system designs, energetically or exergetically;

(d) Design tariffs that induce systems to he more exergetically efficient.


•

•

7.2.3 Demonstration of the impact of exergetic considerations on the

planning process ofdectric energy ~'Ystems.

The :JPplication ofthe exergetic anaIysis in the electric energy systems was tested i., different

cases, namely:

(i) The ana1ysis of the main electric energy system end-uses. (a) space heating, (b)

cooking, (c) water heating, (d) traction, (e) lighting. This ana1ysis was performed for

different system cvnfigurations including the following naturaI resource options:

hydraulic potentiaI, nuclear energy, petroleum, coal and naturaI gas. The limiting

values of FPT and SPT efficiencies were calcu1ated for the most representative

combinations ofend-uses and naturaI resources;

(ü) The e.U:lgetiC and exergetic impact ofperformance improvement (PI) measures at the

residential sector of electric power systems was investigated at different levels,

namely, the electric appliance being improved, the eustomer, the electric and gas/oil

utilities and the overall natural resources. Such PI measures include the introduction

ofmore efficient e1ectrica1 app1iances, water-heaters or light bulbs. Special attention

is devoted to the influence ofheat-gains due to CToss-effects on heating and cooling

loads.

(iü) The energetic and exergetic impact ofa major adoption of eleetric vehicles (EV) in

the Canada energy system was investigated. Different scenarios were evaluated to

sinndat'.l the increased electric demand due to the adoption ofEV technology. These

scenarios inc1ude variations on the system load filetor and changes in the electric load,

including the adoption ofmore efficient energetica11y and exergetica11y space heating

alternatives. The amount ofpetroleum that would be disp1aced ifEY were adoptee!,

as we11 as the demand to build new powergenerationuuitswere evaluated. Simulation

ofthe simu1taneous adoption ofEY and more exergetica11y efficient ~heating

devices was performed. It was shown that the need to bui1d new e1ectric energy


•

•

generation fàcilities is nonexistent for most of the Canadian provinces ifa fraction of

the space heating loads were converted to direct oil/gas space heating fumaces (e.g.,

27"10 for Québec) or to more efficient options ofspace heating.

7.2.4 Integration ofenergetic, exergetic and economic analysis.

The integration of energetic, exergetic and economic analysis was performed for a space

heating system with four different alternatives: electric baseboard, ground-to-air heat-pump,

air-to-air heat-pump and direct fossi! fuel heating. The design was based on the minimization

ofthe energetic or exergetic consumption at the natura! resource level and the cost to the

customer as weIl as combinations ofthese fàctors.

In order to ensure that the system design corresponds to the minimum exergy solution, it was

hypothesized here that the given energy end-uses will be met by those alternatives that

minimize the cost to the customers. In other words, the end-users of energy will tend to

choose the cheapest alternatives according to their Iifetime costs.

Thus, different cost incentives were tested, for three different regions, that is New Yorlc,

Québec and Ontario, in order for the minimum exergy and minimum cost solutions to be

identical. The costs' incentives studied were subsidies in the initial capital cost investment,

opportunity cost rate and the energy tariffs. Although the minimum exergy solution couid be

achieved with different combinations ofsubsidies, those involving only subsidies related to

capital investments appear to be easier to implement.

• Conclusions and Recommendations for Future Research

7.2.5 Energetic and exergetic regïonal optimization studies.

168

•

•

A series ofsimulation was carnee! out on the optimum planning ofa regional energy system

composee! ofthe Canadian provinces ofQuébec and Ontario. The system was ree!esignee! by

minimizing the total energetic or exergetic consumption at the natural resources level. These

optimum designs are then comparee! with each other and with the existing 1995 system.

This study encompasses five types ofnatural resources ( hydre, nuclear, petroleum, natural

gas and coal) and five types ofend-uses ( space heating, cooking, water heating, traction and

lighting), as we11 as sorne intermedia%e conversion processes such as: power plants, refineries

and energy transportation and transmission systems.

A series ofoptimal regional planning studies was performee!. Two main objective funetions

were usee!, that is, the minimization ofthe energetic and the exergetic resources at the system

level. It was demonstratee! that the optimization performee! on the basis ofthe Fast Principle

alone does not in general maximize the exergetic resources in a multiple end-use and naturaI

resources constrainee! case.

The influence ofincreasing the capacity ofthe transmission line connecting the two provinces

was testee!. It is shown that the ideal transmission line capacity is different (aImost double)

if the objective funetion for optimi7Jltion purposes is changee! from minimum exergy to

minimum energy consumption at the resource level. Thus, the minimum exergy solution

requires a lower investment in transtnission lines.

The adoption of a minimum exergy solution was comparee! to the 1995 energy/exergy

consumption Ievels. It was notee! that ail available e:œrgetically efficient end-use devices were

part ofthe optimal solution. This implies a switch to direct heating fumaces, efficient motors

and Iighting to supply the end-use demand. On the other hand, options such as e1ectric


•

•

baseboard and, electric water heaters were not chosen by the optimization procedure. It is

aIso interesting to note!hat no nuc1ear, oil, coal or natura! gas power-plants were necessary

for both provinces in the minimum exergy case. It was shown that the adoption of the

minimization ofthe exergetic resources wouid save approximately 23% ofthe 1995 energy

consumption or nearly of 10,000 MW ofthermoelectricity generation.

The resuIts ofoptimizing the system by minimizing the exergy at the natura! resource level

shouid he seen as a long term goal rather!han a plan ofaction to be implemented in the short

term.

A sensitivity analysis was petformed by the examination ofthe Lagrange muitipliers caIculated

in the optimization process. T1üs analysis a:Jows the ellergy planner to rank the relative

incremental impact ofincreasing the Iimits ofthe outputs ofthe various end-use devices in the

overaIl SPT or FPT efficiencies. The sensitivity analysis showed !hat the relaxation on the

end-use device Iimits is incrementally, a more efficient measure !han the relaxation ofthe

hydro resources in Ontario or the increase in the transmission line Iimit connecting Québec

to Ontario. However, it is known !hat the relaxation on some ofthe upper bounds is not a

simple task when compared to the increase ofthe transmission line levels connecting the two

neighbouring systems.

It is important to point out that the overaIl SPT efficiency couid he substantially increased by

other means !han the ones mentioned above. T1üs wouid he possible, for example, ifother

types ofend-uses such as the end-use road transportation couid he supplied massively by

electric traetïon. Ifthis were done without changing substantially the generation Iimits, then

part ofthe end-uses devices must change to more exergetically efficient alternatives and al

the same lime release some electric power.


•

•

7.2.6 A proposition of a new kind of e1ectric rate, type-of-use tariffs,

that incorporate exergetic considerations.

This thesis discusses a proposition ofa type oftariffbased on the type-of-use, as opposed to

ilie more common time-oj-use tariflS. The main motivation for introducing type-oj-use tariffs

is to force the system to maximize ifs 0vera1l exergetic efliciency. Simulations were performed

to test different tariffstructures to accomplish tlùs objective in the regional planning basis.

It was demonstrated that it is possible to achieve the minimum exergy solution by the proper

choice of the weighting factors in the objective function. The weighting factors are

proportional to the inverse ofthe Second Principle efficiency for end-use deviees and to the

inverse ofthe fraction ofavailable wade (exergy) for natura! resourees. The weighting factors

are rationalized as type-oj-use tariffs. It is believed tbat type-oj-use tariffs might be

implemented in steps starting, for example, with ooly two or tbree categories such as heat

related and non heat related loads. As metering technologies and other resulation constraints

permit, other type-oj-use categories could he implemented. This is analogous to migrating

from time-oj-use, with ooly two periods, to hourly spot priees. The main motivation for

introducing a type-of-use tariff is to force the system to maximize its overall exergetic

efficiency.

The impact ofthe adoption oftype-oj-use tariffs in the different economic sectors will result

in an 0vera1l smaller tariffburden to those sectors aIready using traction as a major end-use.

This is the case in the industrial sector as opposed to residential and commercial sectors.

• Conclusions and Recommendations for Future Research

7.3 Recommendations for Future Work

• Exergetic analysis and Integrated Resources Planning (IRP)

171

•

The scope ofelectric energy plamùng should as much as possible encompasses other loads

not usua\Iy considered 50ch as the end-use road transportation.

Som~ ofthe changes srlpulated by the minimum exergy solution such as the declined use of

nuclear power plants and thermoe1ectric systems involve additional economic, politica\ and

social considerations which must be carefully analysed.

The relationship exergetic :malysis and environmental concerns must be further studied. The

general public should be made aware about the relevance of exergetic analysis in energy

systems.

• End-use forecast by economic sectors

The load forecast needs to be performed in terms of end-uses for each of the economic

sectors (residential, commercial and industrial). Today, for the most part, only the residential

sector's forecasts are performed in terms ofend-uses. The commercial and industrial sectors'

forecasts have net been ana\ysed according to their end-use, but rather in terms ofthe energy

consumption oftheir 5Ob-sectors.

• Tests oftype-of-use tarilTs

Simulations ofthe influence ofthe adoption of type-of-use tarifiS are required in order to

fuIIy comprehend their impact in the patterns ofenergy consumption and their influence and

he1p the system te become more exergetically efficient. Different type-of-use schemes should


•

•

he tested including different end-use sets such as heat-related-loads, traction and Iighting. The

simulations of type-oj-use must involve evaluations by ecollOmiC sector such as industrial,

commercial and residential. Certainly a pilot ccperience with type-oj-use tariffs will shed more

light into its relevance and practicality for inducing exergetically more efficient systems.

•

•

•

References

References

Almeida, K. C., (1994), A General Parametric Optimal Power Flow, Department of

Electrical Engineering, McGill University, PbD thesis, 299 p. Montréal, Québec, Canada.

Alvarez, C., Be1enguer, E. (1993), "Object Oriented Environment for Distribution

Applications", llth Power Systems Computation Conference, Volume 1, pp. 155-161,

Avignon, France, September.

Amann, C. A, 1990, "Technical Options for Energy Conservation and Controlling

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•

•

First and Second Principle Efficie:1cies for Different System Configurations

AppendixA.

First and Second Principle Efficiencies for

Different System Configurations

184

• First and Second Principle Efficiencies for Different System Configurations

Table Al. FPT efficiency, TJ, ofend-use devices for various system configurations (%).

185

•

•

1

End-use device [ Oil

1Gas

1

Coal [ Nuclear [ Hydro

1

1. Space heating fumace 57.2 57.2 57.2 n.a n.a.

2. Baseboard 31.0 31.7 31.4 31.4 87.4

3. Heat-pump air-to-air 52.7 53.9 53.3 53.3 148.6

4. Heat-pump ground-to-air 79.4 81.1 80.3 80.3 223.7

5. Direct coolàng fumace 33.7 33.7 33.7 n.a n.a.

6. E1ectric cooking 15.8 16.2 16.0 16.0 44.6

7. Direct water-heating fumace 40.8 40.8 40.8 n.a n.a.

8. Electric water-heating 26.7 27.2 27.0 27.0 75.2

9. Efficient motor 24.8 25.3 25.1 25.1 69.9

10. Inefficient motor 18.6 19.0 18.8 18.8 52.4

11. Inefficient lighting 1.9 1.9 1.9 1.9 5.2

12. Efficient lighting 6.2 6.3 6.3 6.3 17.5

• First and Second Principle Efficiencies for Different System Configurations

Table A2. SPT efficiency, €, ofend-use deviees for various system configurations (%).

186

•

•'"

End-use Deviee Oil Gas Coal Nuclear Hydro

1. Space heating fumace 3.9 3.9 3.9 n.a. n.a.

2. Baseboard 2.1 2.1 2.1 2.1 2.5

3. Heat-pump air-to-air 3.6 3.6 3.6 3.6 4.2

4. Heat-pump ground-to-air 5.4 5.5 5.4 5.4 6.4,

'.5. Direct cooking furnace 10.1 10.1 10.1 n.a. n.a.

6. Electric cooking 4.8 4.9 4.8 4.8 5.6

7. Direct water-heating fumace 8.2 8.2 8.2 n.a. n.a.

8. Electric water-heating 5.3 5.5 5.4 5.4 6.3

9. Efficient motor 62.0 63.4 62.7 62.7 73.6

10. Inefiicient motor 46.5 47.5 47.0 47.0 55.2

11. Inefiicient lighting 0.2 0.2 0.2 0.2 0.3

12. Efficient Iighting 2.3 2.4 2.4 2.4 2.8

•

•

•

Energetic and Exergetic Savings at DifferentSystem Levels for DSM Performance Improvement

Appendix B.

Energetic and Exergetic Savings at

Different System Levels for

DSM Performance Improvement

(i) Efficient electric water heater (Tables B.I and B.2);

(ii) Replacement of incandescent by compactfluorescent Iight bulbs (Tables B.3 and BA).

187

• Energetic and Exergetic Savings at DifferentSystem Levels for DSM Performance Improvement

188

•

•

Table BI. Energetic savings at different system levels for PI 'Efficient Electric WaterHeater'.

Energy savingsin equivalent kWblyear/customer

ConfigurationAppliancc Cooling Spacc DweUing E1cetric Gas/Oil Net

Hcoting Uli1ity Uli1ity ResourccSnvings

CI 438 36 -287 187 219 0 219

C2 438 36 -96 378 443 0 443

C3 438 36 -355 119 555 -401 154

C4 438 36 -287 187 631 0 631

CS 438 36 -96 378 1278 0 1278

C6 438 36 -355 119 1600 -401 1199

Table B.2 Exergetic savings at different system levels for PI 'Efficient Electric Water Heater'.

Exergysavingsin equivalent kWblyear/customer

PmfigurationNet

Appliancc CoolingSpacc

DweUingE1cetric Gas/Oil

ResourccHcating Uli1ity Uli1itySnvings

CI 416 34 -273 177 208 0 208

C2 416 34 -91 359 421 0 421

C3 416 34 -BI 319 527 -148 379

C4 416 34 -273 177 233 0 233

CS 416 34 -91 359 473 0 473

C6 416 34 -131 319 592 -148 444

• Energetic and Exergetic Savings at DifferentSystem Levels for DSM Performance Improvement

189

•

Table B.3. Energetic savings for PI 'Replacement ofIncandescent by Compact FluorescentLight Bulbs'.

Energy savingsin cquivalcnt kWhlycar/customcr

ConfigullltionGas/Cil Net

Appliancc CoolingSpacc

Dwclling E1cctric Utilily RcsourccHcating Utilily Savings

Cl 51S 40 -322 236 276 0 276

C2 51S 40 ·107 451 527 0 527

C3 51S 40 -397 161 653 -454 19S

C4 51S 40 ·322 236 g06 0 S06

C5 51S 40 -107 451 1539 0 1539

C6 51S 40 -397 161 1905 -454 1451

Table B.4 Exergetic savings for PI 'Replacement ofIncandescent by Compact FluorescentLight Bulbs'.

Energy savingsin cquivalcnt kWhlycar/customcr

ConfigurationGas/o.1 Net

Appliancc CooUng SpaccDwcIIing

ElcctricUtilily Rcsourcc

Hcatin8 Utilily Savinga

CI 493 38 -306 22S 263 0 263

C2 493 38 -lm 429 501 0 SOI

C3 493 38 -147 384 6.."0 -168 452

C4 493 38 ·306 22S 298 0 298

cs 493 38 -102 429 569 0 569

C6 493 38 ·147 384 705 ·168 S37

•

•

•

Estimation of the End-uses for Ontario and Québec in 1995

Appendix C.

Estimation of the End-uses for

Ontario and Québec in 1995

190

• Estimation of the End-uses for Ontario and Québec in 1995 191

C.l Ontario End-uses

C.l.l Space-heating end-use in Ontario

The end-use space heating for Ontario was calculated considering that:

(i) The space heating alternative non-forced air was considered to have the efficiency of

the e\ectric baseboard,

(ü) The proportion of the different space heating alternatives in the commercial and

industrial sectors were assumed to be the same as the residential sectors.

Table C.l Energy consumption for the space heating end-use devices in Ontario, 1995.

Non-Direct Hc:lt Hc:lt-

forccdoiVgas Pump pump Totll1

Scctor air air- ground-Oil Gas to-air to-air

Encrgy supplicd, 7066 9167 36782 415 130 53560GWh

Eflicicncyt, % 100 73 73 170 256 78l. Residential

End-use, GWh 7066 6692 26851 623 333 41565% 17 16 65 2 1 100


2. CommcrciaI 3920 14327 1058 196 59 19599End-use, GWh% 20 73 5 1 0 100


3. Industria1 5322 19453 1437 266 80 26558End-use, GWh% 20 73 5 1 0 100

. . .t for the hcat pumps the cfliClcncy IS the cocfliClent-of-pcrformance.Sourcc::(Gclbard & Li 1993ab; Zhu & Lodola, 1993a,b,Low, 1993ab].

•


C.l.2 Cooking end-use in Ontario

The end-use cooking for Ontario was calculated considering that:

(i) The energy conversion device nùcrowave was considered together with electric

ranges,

(ii) The end-use cooking at the industriai sectcr was Cl),1SÏdered to be 50% ofthe food

and beverage industriai sector electric demand.

Table C2 Energy consumption for the cooking end-use devices in Ontario, 1995.

Sector Electric Direct GasTotalCookinll:

Energy1771 195

1966supplied, GWh

1. Residentiai Efficiency, % 51 43 50

End-use, GWh 903 84 987

% 91.3 8.7 100.0

Energy881 1357

2238supplied, GWh

2. Commercial449 584 1033End-use, GWh

% 44 57 100

Energy 1068 1644 2712supplied, GWh

3. Industriai544 707 1252End-use, GWh

% 44 57 100.Sourcc:[GcIbard& Li, 199300; Law 1993ab; Zhu & Lodola, 1993ab].

•

•


C.l.3 Water heating end-use in Ontario

Table C.3 Energy consumption for the water-heating end-use devices in Ontario, 1995.

Sector Electric Direct Oil orTotalGas heating

Energy supplied, GWh 5392 14589 19981

Efficiency, % 86 52 611. Residential

End-use, GWh 4610 7586 12196%

38 62 100

Energy suppliee!, GWh 1405 3777 5182

2. Commercial End-use, GWh 1201 1964 3165%

38 62 100.Soun:c:[GcIb:llÙ & Li, 1993ab; Zhu & Lodola, 1993ab].•

C.l.4 Lighting end-use in Ontario

The end-use lighting for Ontario was calculated considering that:

(i) The inefficient and efficient lighting energy conversion devices were considered to be

alternatives such as incandescent and fluorescent or lighting respectively.

(u) The proportion the efficient and inefficient lighting energy conversion devices in the

industrial sector were considered to be the same as in the commercial sector.

•

Estimation of the End-uses for Ontario and Québec in 1995 194

Table C.4 Energy consumption for the lighting end-use devices in Ontario, 1995.

1Sector

1Inefficient

1

Efficient1

Total1Lighting Lighting



End-use, GWh 259 75 334

% 77 23 100


2. Commercial End-use, GWh 381 1525 1906

% 20 80 100


3. Industrial End-use, GWh 16 377 393

% 4 96 100.SOIl1'CC:[Gclbard & Li, 1993ab; Zhu & Lodola, 1993ab; Low, 1993ab].•


C.l.5 Traction end-use in Ontario

The end-use traction for Ontario was caIculated considering that:

(i) The efficiency and proportion of the efficient and inefficient motor for each ofthe

sectors were assumed;

(ù) The proportion the efficient and inefficient lighting energy conversion devices in the

industrial sector were considered to be the same as in the commercial sector.

Table C.S Energy consomption for traction end-use devices in Ontario, 1995.

1Sector

1

Inefficient1

Efficient1

Total1motors motors



End-use, GWh 72824005 3277

% 55 45 100


Efficiency, % 72 80 752. Commercial

End-use, GWh 121887313 4875

% 60 40 100


Efficiency, % 79 89 873.Industrial

End-use, GWh 346496930 27719

% 20 80 100.Sourcc:[Gclbard & Li, 1993ab; Zhu & Lodola, 1993ab; Law, 1993ab).

•

•

• Estimation of the End-uses for Ontario and Québec in 1995

C.2 Québec End-uses

196

•

•

Sï.'1ce the efficiency ofthe typica1 energy conversion device for the different end-use was not

available for the province of Québec, then the correspondent values of the province of

Ontario were assumed, for the Tables C.6 to C.IO.

<:2.1 Space heating end-use in Québec

Table C.6 Energy consomption for space heating end-use devices in Québec, 1995.

Non- Direct Beat Beat- Totalforced oiVgas Pmnp pump

Scclor air air- ground-OiJ Gas to-air to-air

Energy supplicd, GWh 22978 4342 6512 336 87 34254

Efficicncy'. % 100 73 73 170 2S6 931. Rcsidcntial

End-use, GWh 22978 3169 4754 5n 222 31694

% 73 10 15 2 1 100

Energy supplicd, GWh 8173 . 15806 5598 99 28 29704

2.Commcrciai End-use, GWh 8173 11538 4086 168 72 24038

% 34 48 17 1 0 100

Energy supplicd, GWh 5711 11045 3912 69 20 20757

3. Industrial End-use, GWh 5711 8063 2856 118 50 16798%

34 48 17 1 0 100t for the heat pomps 1he cflictency IS the eocfIiClent-of-performance.Souree:(SlatislcsCanada. 1994; Québec 1993; Québec. 1995].

C2.2 Cooking end-use in Québec

The avaiIable data for the end-use cooking for the province of Québec do not include,

explicitly, data for the commercial and industria1 sectors. For this reason, Table C.7 presents


data for cooking only for the residential seetor.

Table C.7 Energy consumption for the cooking end-use devices for the residential sector in

Québec, 1995.

1Item L~leetric

1Gas

1Total

1


Residential Efficiency, % 51 43 51

SeetorEnd-use, GWh 643 2 645

% 99.7 0.3 100.0..So=:[St:lUSl1cs Canada, 1994;Qucbec: 1993; Qucbec, 1995].

• C2.3 Water heating end-use in Québec.

Table C.S Energy consumption for the water heating end-use devices, for the residential andcommercial seetors in Québec, 1995.

Direct

Item Eleetric oiVgas Total

Oil Gas

Energy supplied, GWh 9000 1973 2960 13933

Efficiencyt, % 86 52 52. 741. Residential

End-use, GWh 7695 1026 1539 10260%

10075 10 15

Energy supplied, GWh 1800 4059 1438 7296

2. Commercial E".1d-use, GWh 1539 2111 748 4397%

35 48 17 100. .t for the hcat pumps the efiiCtCDCY IS the coefiiCtCDt-of-perfonn:mcc.Souroe:[Statistics Canada, 1994;Québec: 1993; Québec, 1995].•


C.2.4 Lighting end-use for Québec in 1995.

Table C.9 Energy consumption for the Iighting end-use in Québec, 1995.

ItemInefficient Efficient TotalLighting Lighting



End-use, GWh 221 65 286%

77 23 100


2. Commercial End-use, GWh 192 769 961%

20 80 100


3. Industrial End-use, GWh 13 312 325%

4 96 100. . .Sourcc:[StatJstics Canada, 1994;Qucbcc 1993; Qucbcc, 1995).

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C.2.5 Traction end-use for Québec in 1995.

Table C.IO Energy consumption for traction end-use devices in Québec, 1995.

SectorInefficient Efficient

TotalMotors Motors



End-use, GWh 2817 2305 5123

% 55 45 100


Efficiency, % 72 80 752. Commercial

End-use, GWh 5964 3976 9941

% 60 40 100


Efficiency, % 79 89 833. Industrial

End-use, GWh 21887 14591 36479

% 20 80 100. . . .Sourcc:[Statisbcs Canada, 1994;Qucbec 1993; Qucbcc, 1995].

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