Integrated Assessment Tools for Network Investments in volatile Market Environments

Transcription

1 Integrated Assessment Tools for Network Investments in volatile Market Environments Christoph Weber EWL - Chair of Management Sciences and Energy Economics, University of Duisburg-Essen Head: Prof Christoph Weber Team: 12 researchers + secretary Chair at the Department of Economics Christoph Weber holds degree in engineering Key Research Areas: Energy & risk management, Investment under uncertainty, Integration of renewable energy sources, Workable competition Energy demand and energy efficiency Projects with/for: EU, Federal and Regional ministries Utilities 1

2 European Electricity Markets Liberalization and increasing Trading Climate Policy and increasing shares of fluctuating renewables 3 Increasing need for new transmission lines Avoid bottlenecks Allow full usage of wind and solar energy Increase market efficiency Improve reliability Save costs? 4 2

3 Overview 1 Introduction 2 Existing European Projects: EWIS and SUPWIND 3 Methodological Approach 4 Results 5 Steps ahead 5 SUPWIND Decision Support for Large Scale Integration of Wind Power Project supported by EU DG Tren

4 Database and Models Wind and demand data Scenario Tree Tool STT Wind & Load & Outage Scen; Reserve Demand Input data base European Electricity Market Model E2M2s Generation Capacities; Seasonal Hydrores Planning; Internat Electricity Exchange Joint Market Model JMM Electricity Prices; Cross-border Elec Exchange Scheduling Model SM Unit Commitment; Reserve Usage Output data base EWIS European Wind Integration Study European TSOs engaged in EWIS, a collaborative effort aiming at thourough examination of RES integration in the European Grid Supported by the EU Supplier for market analysis studies and associated services selected in competitive bidding procedure: SUPWISCI: Scientific partners of SUPWIND consortium 8 4

5 Key challenge for EWIS study Dealing simultaneously with large interconnected transmission systems with multiple generation units, detailed unit commitment and dispatch schedules, stochasticity of wind and corresponding reserve requirements, competitive markets and cost aspects, evolving renewable and conventional power plant portfolios Use of a consistent set of models 9 Overview 1 Introduction 2 Existing European Projects: EWIS and SUPWIND 3 Methodological Approach 4 Results 5 Steps ahead 10 5

6 Database and Models Wind and demand data Scenario Tree Tool STT Wind & Load & Outage Scen; Reserve Demand Input data base European Electricity Market Model E2M2s Generation Capacities; Seasonal Hydrores Planning; Internat Electricity Exchange Joint Market Model JMM Electricity Prices; Cross-border Elec Exchange Scheduling Model SM Unit Commitment; Reserve Usage Output data base European Electricity Market Model E2M2s Flexibel Model currently covering European countries Includes electricity and district heating markets Variable degree of detail: whole of Europe or European regions or/and several regions within one country High temporal resolution: Electricity is not storable Individual hours have to be considered Hydro storages and other technologies require modelling of full years Typical days and typical hours as approach Stochastic modelling of wind and water fluctuations - Increasing share of wind power production in European System - Fluctuating wind power induces additional load flows - Changes in hydrological conditions have also to be foreseen 6

7 Geographical Scope E2M2 S - Input Data on - existing capacities for conventional power plants, renewables and storage - power plant efficiencies - further technical parameters (availability, start-up costs) - grid transfer capacities Scenarios on - fuel & CO 2 -prices - Load - RES-E extension 7

8 E2M2 S - Output Operation of power plants in each country - During typical hours and typical days - Annual Power and Heat Production - CO2-Emissions Investment in new power plant capacities in each country Trans-border power flows - During typical hours and typical days - Also display for each hour of year possible Electricity prices for each country - Base price - Peak price - Prices for typical days and typical hours System cost and differences in system cost between scenarios E2M2 S - Methodology Minimization of system costs - Corresponds to market outcomes in workable competition Dynamic recursive optimization for modelling years - Optimal operation of conventional units with start-up costs etc - Optimal use of hydro reservoirs - Optimal CHP operation - Optimal investment Cost components taken into account - Fuel cost - Other variable cost (eg desulphurization) - CO 2 cost - Investment cost - Other fixed cost (eg staff, insurance) 8

9 Why using an optimisation model? The interdependency of energy demand and supply in different regions and at different moments of time can be modelled in an optimisation to account for storage adequately Combination of different effects can be modelled in an optimisation model in a methodologically sound way Why using a stochastic optimisation model? Certain RES-E and the spot market prices show major stochastic fluctuations not possible to account for in a deterministic cost-curve or optimisation approach "Extreme hours" resulting in binding "bottle-necks" can also be modelled, on which the value of transmission grid investment depends strongly Highlights of E2M2s and SUPWIND approach Detailed modelling of typical days (or even all days in a year) Detailed modelling of CHP Detailed modelling of wind and water stochasticity Detailed modelling of reserve requirements Optional: Modelling of load flows using DC-approximation 18 9

10 Typical days and typical hours Trade-off between required detail and computational burden Currently: 12 typical days For each two months: January/February, March/April, Weekday and weekend within these months 12 typical hours in each typical day Each one representing two hours 19 E2M2 S : RES-E availability stochastic scenarios 1 2 Wind power availability Wind speed data from several measurement points per country, hourly time series for three years available Typical power curve for wind turbines Calibration on annual total wind generation Currently three scenarios per time step, from almost no wind to full power Transition probabilities derived from wind speed data: eg with some likeliness after full wind there will be very little wind Hydro availability In the case of hydro storage plants especially the long-term fluctuations are relevant Fluctuations of 20 % or more may occur between one year and another Cases with low water inflow are most critical Currently two scenarios corresponding to rather low and just above medium water inflow 10

11 E2M2 S : RES-E availability stochastic scenarios High wind Average to high water s s Low wind High wind Low water Low wind day 1, hour 1 day 1, hour 2 day 1, hour 3 s s day d, hour h day d, hour h+1 Modelling of CHP Currently 99 different power plant types in model Of which about 60 are CHP Distinction by Fuel used Technology Type (Backpressure, Extraction Condensing, Gas Turbines, Internal Combustion, ) vintage Modelling of heat regions within countries Germany currently 16 heat regions E g Berlin, Munich, Hamburg, Mannheim But also distinguishing regions using cheap fuel and those using expensive fuel (gas, fueloil) 22 11

12 Modelling of reserve requirements Key requirements Sufficient short term reserves Spinning reserves (primary and secondary reserves) needed in each time period Sufficient overall capacities Non-spinning reserves (tertiary reserves) required in addition to operating plants in maximum to ensure system reliability as specified through a Loss of Load Probability Two corresponding constraints integrated in system optimization Required capacity for system reliability determined by convolution of - Plant availability distribution - Wind variation distribution - Load fluctuations distribution 23 Market and Load-flow modelling: NTC-based calculations vs Load-flow-algorithms NTC-based calculations correspond to results of market mechanisms in place today Basic laws of load flow (Kirchhoff s laws) may be violated in this case Inclusion of DCLF provides improved approximation of actual load flows Market mechanisms might evolve in this direction (eg Market Coupling NL-B-F-D) Use of both methods allows to assess impact of different market designs 24 12

13 Database and Models Wind and demand data Scenario Tree Tool STT Wind & Load & Outage Scen; Reserve Demand Input data base European Electricity Market Model E2M2s Generation Capacities; Seasonal Hydrores Planning; Internat Electricity Exchange Joint Market Model JMM Electricity Prices; Cross-border Elec Exchange Scheduling Model SM Unit Commitment; Reserve Usage Output data base JMM Joint Market Model & Scheduling Model Hourly optimisation of the unit commitment: Detailed description of power plant operation, transmission and demand Market prices correspond to marginal costs of generation Objective function minimises the total operation costs considering endogenously different wind power and load forecast scenarios Further consideration of: Part-load operation with reduced efficiency Start-up Lead-times CHP operation Electricity and heat storages Subdivision of considered countries into model regions to reflect bottlenecks in the transmission grid and concentrations of installed wind power Stochastic input Short-term forecasts of wind power and load Demand for replacement reserves 26 13

14 Stochastic consideration of scenarios Improve decision making by using information contained in stochastic forecasts (eg of wind power production): Expected value of forecast, but also the distribution of forecast errors Sequence of decision making: Decisions with uncertain forecasts: Day-ahead scheduling Decision after realization is known: Down/up regulation of power plants Advantage: Model makes unit commitment and dispatch decisions being robust towards forecast errors 27 JMM - Stochastic Optimization Hour 12 Hour 18 DAY 0 Hour 00 Rolling planning To circumvent non-manageable problem sizes Adequate especially in systems with differential constraints (thermally dominated systems) In hydro-based systems combination with Stochastic Dynamic Programming approaches necessary (cf Pereira 1996, Ravn 2006) Replanning corresponds to arrival of new information Power can be offered at day-ahead and intra-day market Hour 06 Hour 12 DAY 1 DAY 2 Day-ahead market is only operating once a day (in hour 12) 28 14

15 Highlights of JMM Detailed modelling of rolling planning Detailed modelling of CHP Detailed modelling of wind, load and outage stochastics Detailed modelling of reserve requirements Optional: Modelling of load flows using DC-approximation 29 Overview 1 Introduction 2 Existing European Projects: EWIS and SUPWIND 3 Methodological Approach 4 Results 5 Steps ahead 30 15

16 Data Data on Source Resolution Fuel& CO2 prices IEA Yearly Load profiles UCTE/ Nordel Hourly Annual Load UCTE/ TSO data Yearly RES-E Deployment Green-X Yearly Hydro inflow Marketskraft/ national Hourly/ yearly statistics Reservoir levels Marketskraft / national Seasonal statistics Conventional power plants Platts database/ own Single plant research Technical parameters Academic literature Single plant Heat load National statistics Hourly Wind generation Tradewind project/ Hourly national statistics 31 Development fuel prices 32 16

17 Increase in wind capacities Conflict scenario Base prices in Europe

18 Conflict scenario new capacities in europe 35 Conflict scenario total production in Europe [TWh] 36 18

19 Yearly cross-border electricity exchange

20 Scenario enhanced grid 39 Welfare effects 2020 due to additional interconnector capacities in Conflict scenario 40 20

21 Overview 1 Introduction 2 Existing European Projects: EWIS and SUPWIND 3 Methodological Approach 4 Results 5 Steps ahead 41 Challenges Increasing share of electricity generation from renewables in Europe, Australia, North America and worldwide Especially strong increase in fluctuating, supply-dependent production, namely wind energy (and photovoltaics) Challenges for operation of grids and power plants Challenges for planning of grids and power plants Value of fluctuating production and regulation implications? 42 21

22 Grid Operation- Key open questions Optimal planning of reserves with high wind penetration Optimal valuation of storage flexibility with high wind penetration Quality of stochastic/deterministic approximations depending on system characteristics 43 Planning - Key open questions Integration short & long term perspective Generation park adaptation and detailed scheduling under increased wind penetration Integration detailed grid and market modelling for large-scale systems non-linear load flow modelling N-1 and other grid stability criteria Intertemporal scheduling constraints Market clearing and restrictions Iterative coupling and rolling planning required 44 22

23 Integrated Assessment Tools for Network Investments in volatile Market Environments 45 Market Design - key open questions Market design balancing markets with increased wind power Generation park adaptation and detailed scheduling under increased wind penetration Adequate long-term signals in markets Locational signals Capacity scarcity Design of incentives for wind energy Adequate consideration of risks from an investor perspective Compatibility with overall climate policy 46 23