Carlos Santos Silva

2015-2016

Energy Systems Modeling and Economics

Energy Modeling

Reference Energy System

Sustainable Energy System

• To design sustainable energy, several

options must be considered:

• Energy services demand

•Renewable resources

• Energy storage

• Alternative fuels

• To design effectively, the interactions

between the possible options must be

accounted for:

•Consumer behavior

• Intermittency of renewable resources

• Evolution of energy demand/services

• Impact of energy efficiency policies

Planning an energy system

US (2007) US (2025)

Modeling tools for planning

Terminology (1)

•Simulation

• Given sets of data and certain parameters, it simulates the behavior of the system

• Example: How much is the renewables penetration / the cost considering that we have:

• X MW of installed capacity of X1, X2,…XN technologies;

• Y MWh of demand

•Scenarios

• Allows direct comparison between different simulations

•Optimization

• Determines what is the “best” configuration and operation of the system

• Example: What is the installed capacity of X1, X2,…XN technologies, in order to:

• Minimize the cost

• Maximize the renewable penetration

Terminology (2)

•(General) Equilibrium model

• Model that describes the economy by aggregating the behavior of individuals and firms

• In these models, the energy demand is driven by economic variables

• Population evolution, GDP

(Partial) Equilibrium model

• It considers the variation of the price of a single product and the prices of all other products

being held fixed during the analysis

• Only the energy price is varying

Terminology (3)

•Top-down model

• Macro-economic model that describes the interrelationship between labor, capital and

natural resources such as energy.

• The energy demand is driven by economic variables

• Population evolution, GDP

• The interrelationships are modeled with elasticities of substitution.

Bottom-up models

• Detailed technology description (demand and supply), including new technologies

• Energy demand is given or is a function of energy prices and national income (in this case

it will be a partial equilibrium model)

Planning tools @ IST

Analysis of energy planning tools

•Analysis of 84 energy models showed that:

• Simulation and Invesment optimization models are generally used for simulation of

medium and long-term case studies with low resolution

• Operation optimization and Operation and investment optimization models are generally

applied to case studies with higher time-resolution than 1h.

Lack the ability to look

into several years

Modeling gaps

Tools have very different scopes, resolution and algorithms.

Hour Year

Region /Country

House /Neighborhood

Second

Spatial

resolution

Temporal

resolution

Scenarios

Optimization

Methodology

Lack the ability to account

for hourly dynamics

Solution

Hour Year

Region /Country

House /Neighborhood

Second

Spatial

resolution

Temporal

resolution

Scenarios

Optimization

Methodology

Methodological thinking

•In order to reduce the computational complexity of the problem, the proposed

methodology consists in the use of two different tools.

Medium-term model

•Multi-year optimization of investments in renewable energies

•Some hourly dynamics

•Detailed description of energy consumption:

•Across different sectors

•Different types of energy carriers

•Capable of understanding the evolution of the system:

•Economic growth

•Fuel prices

•Energy demand

Short-term model

•Hourly optimization of electricity production for one year, taking into account:

•Start-up costs and efficiencies for thermal engines

•Variability of renewable resources

•Solar

•Wind

•Hydro

•Fuel prices

•Demand profiles

•Dynamic demand options (EVs, others)

•Optimization of use of energy storage systems

Test feasibility

of the results,

one year at a

time

Introduction of

restrictions for

optimization of

investments

Results for São Miguel, Azores

HybridTraditional

Results for Portugal

HybridTraditional

Modeling energy systems

Choose planning tool and evaluate the results

Define reference energy system and calibrate model

Define scenarios that describe possible system evolution

Iterate scenarios to achieve goals, make a sensitivity analysis, make a reality check of the goals

Define policy goals that we want to achieve

FINAL PROJECT

Design a energy policy plan for an energy system

•Contribute to the energy policy for one island of Azores for 2020 to achieve

• 75% of renewable electricity

• 40% of renewable energy on primary energy (considering fossil fuel

substitution)

Topic Island

Electrification of gas consumption São Miguel

Electrification of gas consumption

Pump-storage

Terceira

Interconnection Faial

São Jorge

Pico

Santa Maria

Graciosa

Flores

Pump-storage

Demand response

Corvo

Working projects

•Azores

• Terceira Island pump-storage

•Portugal

• Impact of solar PV self-consumption

• Buildings Retrofit Strategy

•West Lisbon

• Buildings retrofit

EXAMPLE

Project Corvo

December 30th, 2009

Winter 2009/2010

•7 weeks without LPG supply

Winter supply shortages

•Fuel

•Food

Corvo Island, Azores

Land area: 17 km2

Population (2008): 488

Primary energy consumption (TJ): 21

Renewables penetration in electricity: 0%

Number of vehicles: 93 (40 LDV+22 Pick Ups)

Number of households: 145

Electricity customers: 248

Corvo Energy Outlook

•Fuel transport is very difficult in winter

• Supply disruption every year (butane and diesel for vehicles)

• Butane offset

•Annual Government support

• GPL: 39 000 €

• Diesel: 30 000 € electricity / 12 000 € transport

Electricity Consumption

•Diesel Power Plant

• 4 diesel units (536 kW)

• Peak in 2009 (243 kW)

• Off-peak in 2009 (96kW)

•Residential sector represents 40%

• Detailed survey

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1994 1996 1998 2000 2002 2004 2006 2008

GWh

Losses

Residential

Public Services

Commerce

Industry

Agriculture

Road Transportation

Electricity Consumption Dynamics (Season)

Residential Energy Consumption (Electricity)

Towards 100% renewable (energy)

Butane Offset (residential and commerce)

Solar thermal for Hot Water

Electrify stoves and ovens

Diesel and gasoline Offset (road transportation)

Electric Vehicles

Diesel Offset (Power generation)

Renewables + storage facility

DWH model

Pressupostos

Nº Casas: 150

Nº sistemas: 90 ST (60%) + 60 HP (40%)

Nº de ocupantes por casa: 3

Consumo total aqs /dia/ casa: 120 litros

Solar Collector Storage Tank

Area ᶯ Fluid Volume Uc Power

[m2] % % [l] [W/m2.K] kW

4.2 80 80 Water 200 1,8 2

Sistema solar térmico

Sistema bombas de calor

Heat Pump Storage Tank

COP Power Volume

kW [l]

2.5 1.5 300

Morning

[l]

Evening

[l]

Distributed

[l]

0h-8h 0 0 0

8h-9h 40 0 0

9h-10h 40 20 20

13h-14h 0 0 20

19h-20h 0 40 0

20h-21h 40 40 40

21h-22h 0 20 40

22h- 24h 0 0 0

Perfis de Consumo diário

Caso 1: morning profile (pior caso)

Caso 2: total = distribuição igual de

consumos pelos 3 perfis (33% cada)

(ver tabela abaixo)

Models:

Modelo = Carga de 2012 + (90 casas *Apoio sistema solar) + (50 casas*apoio bomba calor)

• Modelo 1.0 - Carga 2012 + apoio livre

• Modelo 1.1 – Carga 2012+ apoio livre + perdas térmicas nos depósitos

• Modelo 2.0 – Carga 2012 + apoio noite (arranque às 00H)

Capacidade Pico maximo

anual

Diferencial pico

cenário base

Energia anual

consumido

Diferencial anual

energia

Energia media consumida

por dia

kW kW kW MWh MWh kWh/dia

Carga 2012 536 221 0 1372 0 3759

Modelo 1.0 457 236 1508 136 4132Modelo 1.1 471 250 1523 151 4174Modelo 2.0 370 149 1511 139 4141

Capacidade Pico maximo

anual

Diferencial pico

cenário base

Energia anual

consumido

Diferencial anual

energia

Energia media consumida

por dia

kW kW kW MWh MWh kWh/dia

Carga 2012 536 221 0 1372 0 3759

Modelo 1.0 371 151 1508 136 4132

Modelo 1.1 400 179 1520 148 4165

Modelo 2.0 370 149 1519 147 4162

Caso 2: igual distribuição de consumos pelos 3 perfis

Caso 1: perfil de consumo de manhã

Resultados: Semana extrema de Inverno

Pico máximo: 400 kW às 21H

(semana 6)

Resultados: Semanas típica de Primavera

Pico máximo: 265 kW às 22H

(semana 16)

Resultados: Semanas típica de Verão

Pico máximo: 259 kW às 22H

(semana 28)

Resultados: Semanas típica de Outono

Pico máximo: 353 kW às 22H

(semana 48)

Is it possible?

•Is it technologically feasible?

• Which type of renewables?

• How much installed capacity of each?

•Is it economically feasible?

• How much does it cost?

• Positive net present value?

Energy system modeling

HOMER (electricity)

ENERGYPLAN (energy)

Modeling approach

•Build reference case

• Calibrate model with reality

• Use Energy balance data, Demand data, Production data

•Build future reference case

• Forecast of demand, fuels costs

• Implement investment plans already settled

•Scenario analysis

• New technologies / installed capacities

• Different optimization strategies

• Different prices

• Different policies

Energy Plan

http://www.energyplan.eu/

EnergyPlan RES

Corvo RES

General Overview

•Input

•Cost

•Output

•Settings

Data Files Structure

•Distributions

• Demand

• Renewable Resources

•Data

• RES model

•Cost

Data files

Files describing hourly data from one year

• 8784 hours

• txt files (tab delimited)

Demands

• % of maximum between 0 and 1

Renewables

• capacity factor

SETTINGS

General Overview

•Capacity Unit

• Scale of the system

•Monetary Unit

INPUT

General Overview

•Electricity Demand

•District Heating

• including Power Production from fossil fuels

•Renewable Energy

•Electric Storage

•Cooling

•Individual

• Residential energy needs

•Industry

•Transports

•Waste

•Biomass

Electricity demand

•Electricity demand

• Total in GWh / year

• 1,37

• Change Distribution

• Corvo_demand.txt

•Electric heating /cooling

• 0

•Flexible Demand

• Energy / Power (1 day / 1 week / 1 month)

• 0

•Fixed Import / Export

• Fixed value

• 0

• Distribution.txt

District Heating

•Distribution of demand

• Distribution.txt

•Distribution of solar thermal

• Distribution.txt

•Group I (no CHP)

• 0

•Group II (small CHP)

• 0

•Group III (large CHP)

• PP2 (560 kWe, 0,3 elect efficiency)

Fossil Fuels

Renewable Energy

•Renewable Energy Source (1 to 4)

• Installed capacity

• Wind (1) – 1000 kW

• Distribution.txt

• Corvo_wind.txt

• Correction factor

• Fine tune capacity factors

•HydroPower

•GeothermalPower

Electric Storage

•Electrolyser

•Electric Storage

(Pump-storage, batteries, Fuel Cell)

• Pump (conversion to potential energy)

• Turbine (conversion to electricity)

• Storage (capacity)

•Advanced CAES

(compressed air energy storage)

Technology evolution

Source: André Pina (PhD MPP-SES)

COSTS

General Overview

•Fuel

•Operation

•Investment

•Additional

Fuel

•Fuel Prices (World Market) € /GJ

• Coal (17.2 /€ bep): 2.8€/GJ

• Oil ( 72 € /bep): 11.8 €/GJ

• Gas ( 47 €/bep): 7.8€/GJ

• Diesel in Corvo: 41 € / GJ

• Use Fuel ENERGYPLAN does not consider diesel power generation plants)

•Handle Costs

•Taxes

•CO2

1 barrel of oil equivalent = 6.1 GJ

Operation

•District Heating

•Power Plants

• PP2: 430 € / MWhe

•Storage

•Individual

Investment

•Wind

• 1.8 M€ /1000 kW

• Period: 25 years

• O&M: 5 %

Solar

• 5M€ /1000kW

• Period:15 years

• O&M: 0

Regulation

General Overview

•Optimization strategy

• Technical

• Market

•Electric Grid Requirement

• Minimum share:0.2

•Critical Excess Electricity Production

• 7 strategies

•External Electricity Market Definition

•External Electricity Market Response

•Transmission line Capacity

• 0

Output

General Overview

•Overview

•Screen

•Graphics

Screen

Graphics

HOMER (Homer LeGACY)

https://homerenergy.com/download.html

General Overview

Electricity “only”!

Equipment

Designing the system

Generator

Wind Turbine

Solar Power Plant

Primary Load

RESOURCES

Solar

Wind

Diesel

System Control inputs

Constraints

Simulation

Results overview

Results detail