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Institute of Power Systems and Power Economics RWTH Aachen University Univ.-Prof. Dr.-Ing. H.-J. Haubrich Forschungsgemeinschaft für Elektrische Anlagen.

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Presentation on theme: "Institute of Power Systems and Power Economics RWTH Aachen University Univ.-Prof. Dr.-Ing. H.-J. Haubrich Forschungsgemeinschaft für Elektrische Anlagen."— Presentation transcript:

1 Institute of Power Systems and Power Economics RWTH Aachen University Univ.-Prof. Dr.-Ing. H.-J. Haubrich Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Current policies and activities to improve the integration of wind energy into the German interconnected system  Generation management of wind turbines  Demand-side management  Improved prediction of load and wind generation  Intraday market and short-term forecasts  Storage commitment  Overhead line monitoring Dipl.-Ing. Philipp Siemes Milan, 8. May 2007

2 1 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. 20052025 19901995 2000 0 10 20 30 GW 50 Year NL GB I DK E D Remain. 43 6 2 3 3 4 4 4 7 24 A F P Wind power installed in Europe Two major impacts of increasing wind power on the established system  Rising demand of control reserve  Increasing network loading

3 2 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Survey of activities to improve the integration of wind energy into the German interconnected system  Generation management (GM) of wind turbines  Potential of demand-side management for provision of control reserve  Improved prediction of load and wind generation  Utilization of Intraday market and short-term forecasts  Storage commitment (Application of Compressed Air Energy Storages)  Overhead line monitoring

4 3 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Reduction of output due to limitation of maximum positive wind forecast error limit of GM wind forecast error 0 h24 h MW 0 h24 h wind power forecast wind power output MW  Low amount of unused wind power  Incentive for improved performance of wind forecast Generation management of wind turbines

5 4 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Potential reduction of control reserve Δ P* [GW] 0 2 4 6 8 10 05 15%2530 wind forecast error / P WP,inst. * Demand of negative control reserve due to the wind forecast error Δ W** [TWh/a] ** Unused wind power due to generation management P WP,inst. = 30 GW P WP,inst. = 48.2 GW increasing generation management Generation management of wind turbines

6 5 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Efficiency of generation management 0 50 100 150 200 250 051015%2530 E* wind forecast error / P WP,inst. GW TWh/a efficiency in case of minimal generation management efficiency in case of entire generation management * Ratio of possible reduction of control reserve to unused energy due to GM Generation management of wind turbines tentative limit of efficiency  High national savings depending on price of control reserve and feed-in tariff

7 6 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V.  Spatial separation of gas turbine in  compressor unit for compression of air  expansion turbine and generator for generation of electric energy  Salt cavern for storage of compressed air  Heat storage for compression temperature in case of adiabatic CAES  Ratio between compressor power, storage capacity and generator power is selectable depending on anticipated application  Key data of commercially available CAES  250 MW compressor power  400 MW generator power  For application as diurnal storage volume of 1.2 Million m³ spread over 3 caverns Components of CAES Natural gas Usage of electric energy Generation of electric energy Cavern Compressed Air Energy Storage

8 7 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Refining of wind power feed-in  Wind power feed-in (P WEA ) is intermittent and stochastic  Combination of wind power feed-in and CAES offers controllable generation capacity  Storage operator takes over the task of refining the wind park‘s feed-in  Wind park has no more demand of control reserve 0 100 200 300 MW 500 0 612h24 P WP P WP+CAES Compressed Air Energy Storage

9 8 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Evaluation of CAES - Attainable profit per application Operating costs Investment costs (above ground) Investment costs (subterranean) Revenues due to Day-Ahead market Revenues due to control reserve 0 20 40 60 M€/a 100 4.. 17 M€/a Refining of wind power feed-in Control reserve 10 M€/a Day-Ahead 2.4 M€/a  No profit by exclusive Day-Ahead commitment  Profits by supply of control reserve for today‘s market prices possible  Refining of wind power feed-in yields additional benefit by prevention of demand of control reserve CAES P Comp = 250 MW P Gen = 300 – 400 MW V Cav = 1.2 – 3.3 Mm³ Compressed Air Energy Storage

10 9 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Overhead line monitoring Transmission capacity depending on wind speed 0% 50% 100% 150% 200% 250% 300% 00.6 (Norm) 2.66.610.614.6m/s22.6 wind speed  Generally big potential for increase of transmission capacity (additional minor influence of ambience temperature and solar radiation)  Possible shielding of conductors from the wind  Dynamic rating regards registration of current conditions  Increase of transmission capacity only useful for network operation, not for planning

11 10 Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Application of seasonal standards (Example of Bremen) 0% 20% 40% 60% 80% 100% 120% 140% Jan.Feb.Mar.AprilMayJuneJulyAug.Sep.Oct.Nov.Dec.  Increase of transmission capacity only useful for network operation, not for planning  No alternative to network reinforcement, but reduction of generation management possible Overhead line monitoring


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