Elforsk 14 juni 2013
Vattenkraften har en centrala roll i kraftsystemet Vattenkraft används för att reglera ut förbrukningsvariationer. 1-7 januari 2011. Reglering med vattenkraft är billig vilket ger stabila priser, 1-7 januari 2011.
Vindkraft leder till ökad prisvolatilitet De ökade reglerbehovet som vinden medför kan i princip hanteras på 4 olika sätt 1. Vattenkraften regleras annorlunda (mera) 2. Värmekraften används för reglering, 3. Utriksehamndeln förändras, och 4. Efterfrågan bidrar till reglering Oberoende av hur reglerbehovet tillfredsställs kommer att krävas ytterligare prisvolatilitet för att motivera ett annat beteende. Storheter: Efterfrågans variation 6000 MW Vattenkraftens variation maximalt ca 10 000 MW Vindkraftens variation (30 TWh) maximalt ca 11 000 MW Import export maximalt ca +/- 5000 MW
Tillräcklig kapacitet i systemet, Med några få undantag får elproducenter bara betalt när man faktiskt producerar Verkligt 2011: 2000 MW användes kortare än 55 timmar 2011 med 30 TWh vind: 2000 MW användes kortare än 35 timmar Inte intressant att ha produktion och nät för så få förväntade timmar
Reglera systemet med låg förbrukning och mycket vindkraft en särskild utmaning Med 2011 års väder och förbrukning samt 30 TWh vindkraft skulle det ha varit ca 20 timmar då nettoförbrukningen understeg vattenkraftens lägsta möjliga produktion. I verkligheten uppstår dessutom stabilitetsproblem när andra kraftverk behöver reglera ner kraftigt.
Decentralize investment decisions and dispatch Investment decisions Annual water planning Service on Nuclear & transmission Day ahead Intra day Gate closure Bids to real time market Purchase disturbance reserve, winter peak reserve Purchase Automatic reserves Managing the system in real time: Automatic resources Manual controlled resources Load shedding 6
The changing nature of the electricity market means we could face significant risks to security of electricity supply in the medium term. As such, The Government will take powers in the Energy Bill to run a Capacity Market. Department of Energy and Climate change, UK
Tre typer av elmarknadsmodeller A. Modell som simulerar investeringar i produktion och nät givet olika restriktioner, redovisar ofta data på årsbasis B. Modeller som simulerar veckomedel pris och produktion för ett givet elsystem men med hänsyn till osäkerheter (probabiistisk), främst tillgången på vatten. C. Modeller som simulerar priser, produktion och handel på timbasis för ett givet system. Förbrukning, vind och tillgång på vatten är given (deterministisk) 8
Sweco s European Power Market Model Sweco s new Power Market model covers the European power market Geographical resolution: country level or price areas (possibility to split countries depending on data availability) Module based set-up allows for flexibility depending on the analysis question. Hourly resolution modelling dispatch Capacity in generation and transmission given Demand, solar and wind power given Many different wind years need to be accounted for. start and stop costs thermal power given weekly hydro power production given, Limitations in min and max Limitation in 1 h change Limitation in 4 h change 9
German generation and trade with Nordic region, January 60 50 40 30 20 Vindkraft 10 0 40 35 30 25 20 15 10 5 0 10 5 0-5 -10 1 101 201 301 401 501 601 701 1 101 201 301 401 501 601 701 1 101 201 301 401 501 601 701 Gasturbiner CCGT och gaskondens Kolkondens Brunkolkondens DK2 DK1 NO2 SE4
Assumptions RES and demand For 2020 RES assumptions close to RES directive in all scenarios. Assumptions 2030 Assumptions 2040 11
Source: Sweco Energy Markets, model simulations 12 Conventional investments, Germany Investments decided by profitability No investments in conventional thermal generation in the Nordic countries too low price level No investments in Germany up to 2020 (in addition of already decided investments) Up to 2030 conventional investments in all three scenarios New capacity to 2030, Germany Installed capacity in 2030, Germany
Source: Sweco Energy Markets, model simulations Profitability of conventional investments - Germany In 2020 CCGTs (and gas turbines) have difficulties covering their fixed OPEX Valid for all three scenarios The most efficient CCGTs barely covers their fixed OPEX Scarcity prices of limited importance in 2020 Only lignite covers CAPEX In 2030 fixed OPEX is covered in all scenarios But CAPEX only covered for the most efficient CCGTs and coal power plants plants in CPI scenario => follows from investments in new generation capacity setting the average price Contribution to CAPEX - CPI, 2020 Contribution to CAPEX CPI, 2030 13
Source: Sweco Energy Markets, model simulations Volatility increases over time in all scenarios - larger difference in zero prices than scarcity prices In 2020 no scarcity prices in the model In 2030 scarcity prices still rare in the Nordics, but more becomes more common in the Continental market In reality there may be more scarcity prices due to combination of events not captured by the model Frequent zero prices in the Continental market already in 2020 Dramatic increase of zero prices in 2030 Large difference between scenarios # scarcity prices, 2030 # zero prices, 2020 # zero prices, 2030 14
Source: Sweco Energy Markets, model simulations The pattern for Germany and NO1 holds also for other countries/areas Small price differences between the scenarios in 2020 Growing price differences in 2030 Significantly lower prices in High RES scenario Very low prices in Norway & Sweden in the High RES scenario Average prices, 2020 Average prices 2030 15
Source: Sweco Energy Markets, model simulations Number of extreme prices increases significantly towards 2030 Scarcity prices, 2020 Zero prices, 2020 Scarcity prices, 2030 Zero prices, 2030 16
Germany CPI year 2020 Generation, trade and prices. Week 4 Average price: 57.9 # shortage hours: 0 # zero prices: 107 Generation, trade and prices, Week 32 Source: Sweco Energy Markets, model simulations 17
Finland CPI year 2020 Generation, trade and prices. Week 4 Average price: 49.4 # shortage hours:0 # zero prices:18 Generation, trade and prices. Week 32 Source: Sweco Energy Markets, model simulations 18
Simulated prices January 2030, SE3, EUR/MWh 0 20 40 60 80 100 120 140 160 180 1 17 33 49 65 81 97 113 129 145 161 177 193 209 225 241 257 273 289 305 321 337 353 369 385 401 417 433 449 465 481 497 513 529 545 561 577 593 609 625 641 657 673 689 705 721 737 Januari
Contact: Peter Fritz Director, Tel: +46 8 695 14 40 E-mail: peter.fritz@sweco.se
Balancing the system Investment decisions Annual water planning Service on Nuclear & transmission Day ahead Intra day Gate closure Bids to real time market Purchase disturbance reserve, winter peak reserve Purchase Automatic reserves Allocate capacity between countries and price areas to day ahead market Re dispatch through counter purchase Managing the system in real time: Automatic resources Manual controlled resources Load shedding 21