Energy Systems Modeling and Economics Energy Modeling. Carlos Santos Silva

Transcription

1 Energy Systems Modeling and Economics Energy Modeling Carlos Santos Silva

2 Reference Energy System

3 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

4 Planning an energy system US (2007) US (2025)

5 Modeling tools for planning

6 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

7 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

8 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)

9 Planning IST

10 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.

11 Modeling gaps Tools have very different scopes, resolution and algorithms. Spatial resolution Lack the ability to look into several years Lack the ability to account for hourly dynamics Region /Country Methodology Optimization House /Neighborhood Scenarios Second Hour Year Temporal resolution

12 Solution Spatial resolution Region /Country Methodology Optimization House /Neighborhood Scenarios Second Hour Year Temporal resolution

13 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 Introduction of restrictions for optimization of investments Short-term model Test feasibility of the results, one year at a time 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

14 Results for São Miguel, Azores Traditional Hybrid

15 Results for Portugal Traditional Hybrid

16 Modeling energy systems Choose planning tool and evaluate the results Define reference energy system and calibrate model Define policy goals that we want to achieve Define scenarios that describe possible system evolution Iterate scenarios to achieve goals, make a sensitivity analysis, make a reality check of the goals

17 FINAL PROJECT

18 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 Electrification of gas consumption Electrification of gas consumption Pump-storage Interconnection Island São Miguel Terceira Faial São Jorge Pico Santa Maria Graciosa Flores Pump-storage Demand response Corvo

19 Working projects Azores Terceira Island pump-storage Portugal Impact of solar PV self-consumption Buildings Retrofit Strategy West Lisbon Buildings retrofit

20 EXAMPLE

21 Project Corvo

22 December 30 th, 2009 Winter 2009/ weeks without LPG supply Winter supply shortages Fuel Food

23 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

24 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: Diesel: electricity / transport

25 GWh Electricity Consumption Losses Residential Public Services Commerce Industry Agriculture Road Transportation Diesel Power Plant 4 diesel units (536 kw) Peak in 2009 (243 kw) Off-peak in 2009 (96kW) Residential sector represents 40% Detailed survey

26 Electricity Consumption Dynamics (Season)

27 Residential Energy Consumption (Electricity)

28 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

29 DWH model Pressupostos Perfis de Consumo diário Nº Casas: 150 Nº sistemas: 90 ST (60%) + 60 HP (40%) Nº de ocupantes por casa: 3 Consumo total aqs /dia/ casa: 120 litros Caso 1: morning profile (pior caso) Caso 2: total = distribuição igual de consumos pelos 3 perfis (33% cada) (ver tabela abaixo) Sistema solar térmico Morning [l] Evening [l] Distributed [l] Solar Collector Storage Tank 0h-8h Area ᶯ Fluid Volume U c Power [m 2 ] % % [l] [W/m 2.K] kw Water 200 1,8 2 Sistema bombas de calor 8h-9h h-10h h-14h h-20h h-21h h-22h h- 24h Heat Pump Storage Tank COP Power Volume kw [l]

30 Models: Modelo = Carga de (90 casas *Apoio sistema solar) + (50 casas*apoio bomba calor) Modelo Carga apoio livre Modelo 1.1 Carga apoio livre + perdas térmicas nos depósitos Modelo 2.0 Carga apoio noite (arranque às 00H) Caso 1: perfil de consumo de manhã Capacidade Pico maximo anual Diferencial pico cenário base Energia anual consumido Diferencial anual Energia media consumida energia por dia kw kw kw MWh MWh kwh/dia Carga Modelo Modelo Modelo Caso 2: igual distribuição de consumos pelos 3 perfis Capacidade Pico maximo anual Diferencial pico cenário base Energia anual consumido Diferencial anual Energia media consumida energia por dia kw kw kw MWh MWh kwh/dia Carga Modelo Modelo Modelo

31 Resultados: Semana extrema de Inverno (semana 6) Pico máximo: 400 kw às 21H

32 Resultados: Semanas típica de Primavera (semana 16) Pico máximo: 265 kw às 22H

33 Resultados: Semanas típica de Verão (semana 28) Pico máximo: 259 kw às 22H

34 Resultados: Semanas típica de Outono (semana 48) Pico máximo: 353 kw às 22H

35 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)

36 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

37 Energy Plan

38 EnergyPlan RES

39 Corvo RES

40 General Overview Input Cost Output Settings

41 Data Files Structure Distributions Demand Renewable Resources Data RES model Cost

42 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

43 SETTINGS

44 General Overview Capacity Unit Scale of the system Monetary Unit

45 INPUT

46 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

47 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

48 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

49 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

50 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)

51 Technology evolution Source: André Pina (PhD MPP-SES)

52 COSTS

53 General Overview Fuel Operation Investment Additional

54 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

55 Operation District Heating Power Plants PP2: 430 / MWhe Storage Individual

56 Investment Wind 1.8 M /1000 kw Period: 25 years O&M: 5 % Solar 5M /1000kW Period:15 years O&M: 0

57 Regulation

58 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

59 Output

60 General Overview Overview Screen Graphics

61 Screen

62 Graphics

63 HOMER (Homer LeGACY)

64 General Overview Electricity only!

65 Equipment

66 Designing the system

67 Generator

68 Wind Turbine

69 Solar Power Plant

70 Primary Load

71 RESOURCES

72 Solar

73 Wind

74 Diesel

75 System Control inputs

76 Constraints

77 Simulation

78 Results overview

79 Results detail