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Economic Potential for an Extension of Pump Storages in Norway

Economic Potential for an Extension of Pump Storages in Norway. IAEE 2011, Stockholm. Tobias Frohmajer Stephan Spiecker Prof. Dr. Christoph Weber. Agenda. Introduction Presentation of the models applied Scenario description Results Conclusions. Agenda. Introduction

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Economic Potential for an Extension of Pump Storages in Norway

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  1. Economic Potential for an Extension of Pump Storages in Norway IAEE 2011, Stockholm Tobias Frohmajer Stephan Spiecker Prof. Dr. Christoph Weber

  2. Agenda • Introduction • Presentation of the models applied • Scenario description • Results • Conclusions

  3. Agenda • Introduction • Presentation of the models applied • Scenario description • Results • Conclusions

  4. Introduction • Rising shares of volatile electricity production from RES in Europe • In the upcoming future, especially the potentials of off-shore-wind power in the north and baltic sea are scheduled to be developed • In order to guarantee serving of the load also in times of lower RES-production, flexible production has to be provided to the grid • Flexibility from flexible power plants (e.g. Natural Gas but also Hydro storages) • Flexibility due to extension of transmission capacities • Flexibility from electricity storages (e.g. Pump storages) • Linking the offshore-production with a north-sea grid to the storage potentials in Norway seem to be of great advantage

  5. Agenda • Introduction • Presentation of the models applied • Scenario description • Results • Conclusions

  6. Agenda • Introduction • Presentation of the models applied • Overview • E2M2s • JMM • Scenario description • Results • Conclusions

  7. Interaction ofthemodels European Electricity Market Model E2M2s Input – database Productioncapacities, seasonalusageofhydrostorages; Type days: Electricityprices, electricityproductionandelectricityexchangebetween countries Output – database Joint Market Model JMM Hourlyelectricityprices, electricityproductionandelectricityexchangebetween countries

  8. Basic considerationsofthemodels (I) • Models of European countries • Including electricity and district heating markets • Variable degree of detail: • whole of Europe or • European regions or/and • several regions within one country • Possible stochastic modeling of wind, solar and water fluctuations • increasing share of solar and wind power production in European System • fluctuating production induces additional load flows • changes in hydrological conditions have also to be foreseen

  9. Basic considerationsofthemodels (II) • Minimization of system costs • corresponds to market outcomes in workable competition • Cost components taken into account • fuel cost for electiricity production and for start – ups • CO2 – costs for electiricity production and for start – ups • other variable cost (e.g. Operation and maintanence) • Further restrictions: • Electricity production from additional RES capacities (wind and solar) • Dispatch of the existing hydro capacities • Grid bottlenecks • ...

  10. E2M2s – Methodology • Long term – investment model • Modelling several years • Representation of each year in typical days and typical hours • Stochastic optimization using recombining trees

  11. E2M2s – Results • Optimal dispatch of production technologies • Optimal investment in power plant capacities • Optimal exchange of electricity • Fundamental prices of electricity production  shadow prices of the demand restriction • CO2-prices  shadow prices of the emission bound • Total system costs

  12. JMM – methodology • Developed within the EU project WILMAR • Applied in the EU-projects EWIS and SUPWIND • Dynamic Stochastic Linear programming approach • Possible to use mixed integer programming approach • Hourly Optimization of 2 markets: • day- ahead (unit dispatch up to 36 hours) • Intraday (redispatching the day-ahead results if new information available) • Recombining wait and see decision structure • Very detailed representation of technical restrictions (e.g. ramp rates; CHP units etc.) • NTC, PTDF and DCLF depiction of the grid is possible

  13. Agenda • Introduction • Presentation of the models applied • Scenario description • Results • Conclusions

  14. Basic considerations • Time horizon: 2030 • Considered overall developments: „Environmental friendly“ • High Prices for fossil Fuels • High CO2-prices • Excessive built-up of RES – capacities • Low development of electricity demand • Successful launch of „Desertec“ supplying annually 180 TWh • Geographic scope: Europe • incl. Norway, Switzerland and 3 offshore-nodes • excluding south-eastern Europe • Representation of Germany in 7 regions

  15. GeographicalScope

  16. GeographicalScope 50HzA TPA TPB 50HzB AMPA EnBWA TPC

  17. Consideredscenarios • Scenario 1: • Moderate extension of the north sea grid • Only 2 offshore nodes • Less installed wind capacities connected to these nodes • More offshore-wind capacities connected bidirectional to the countries • No extension of pumping capacities in Norway • Scenario 2a: • Extensive grid extension • 3 offshore nodes • More offshore-wind capacities connected to the offshore-nodes • Less installed wind capacities connected bidirectional to the countries • No extension of pumping capacities in Norway

  18. Consideredscenarios • Scenario 2b: • Higher grid extension • 3 offshore nodes • More offshore-wind capacities connected to the offshore-nodes • Less installed wind capacities connected bidirectional to the countries • Installation of pump capacities in norwegian hydro reservoirs (9100MW) • Scenario 2c: • Higher grid extension • 3 offshore nodes • More offshore-wind capacities connected to the offshore-nodes • Less installed wind capacities connected bidirectional to the countries • Installation of pump storages in Norway (9100MW)

  19. Agenda • Introduction • Presentation of the models applied • Scenario description • Results • Conclusions

  20. Comparison of average base prices

  21. Comparison of base prices • Scen 1 vs Scen 2a-c: • The price levels are levelising due to the higher transmission capacities • The average base price level in countries linking to NO and SE decrease while the prices in NO and SE itselve do rise • Scen 2a vs 2b vs 2c: • Only marginal differences between the scenarios indicate marginal effects

  22. Comparisonofstandarddeviationsofbaseprices

  23. Comparison of standard deviations of base prices • Similar picture to the previously show base prices • Scen 1 vs Scen 2a-c: • Due to the grid extension, the standard deviation of the base prices is decreasing or stabalized on a low level • Scen 2a vs 2b vs 2c: • Only marginal differences

  24. Electricityproductionsbyfuelandregion

  25. Electricityproductionsbyfuelandregion • While the base scenarios area equal, there are only marginal differences beween the scenarios • The pumps in scenario 2b are not used – in each hour, when the price difference between day and night would be high enought that the pumping would be economic, the turbines are already producing with their full capacity and restrict the production • In scenario 2c, the pumped-hydro storage produces 1.8 TWh per year within 578 hours • In comparison to the total annual production of NO of 157TWh, this is only a percentage of 1.1%  only of marginal influence

  26. Electricityexchangesbetween countries – scenario 1

  27. Electricityexchangesbetween countries – scenario 2a

  28. Electricityexchangesbetween countries – scenario 2c

  29. Agenda • Introduction • Presentation of the models applied • Scenario description • Results • Conclusions

  30. Conclusions • An extension of the north sea grid seams to have greater impact than the additional installation of pumping capacities or pumped hydro storages • The existing hydro storages are already very flexible – a shifting of the production to hours of high prices is already possible and by the extension of the grid even more applicable • An extension of the capacities (pumping as well as production) is useful and dispatched within expected values

  31. Thankyouforyourattention! Anyquestionsorremarks?Contact:Tobias Frohmajer (researchassistantandPh. D. student)University of Duisburg-EssenChairfor Management SciencesandEnergy EconomicsUniversitätsstr. 1245117 Essen, Germanytobias.frohmajer@uni-due.de

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