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EnBW Trading GmbH energy & meteo systems GmbH Dr. Bernhard Graeber Dr. Matthias Lange

Immediate Horizontal Wind Energy Exchange between TSOs in Germany since September 2004 Practical Experiences EWEC 2006, 28 February 2006, Athens, Greece. EnBW Trading GmbH energy & meteo systems GmbH Dr. Bernhard Graeber Dr. Matthias Lange Clemens Krauss Dr. Ulrich Focken . Content.

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EnBW Trading GmbH energy & meteo systems GmbH Dr. Bernhard Graeber Dr. Matthias Lange

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  1. Immediate Horizontal Wind Energy Exchange between TSOs in Germany since September 2004 Practical ExperiencesEWEC 2006, 28 February 2006, Athens, Greece EnBW Trading GmbH energy & meteo systems GmbH Dr. Bernhard Graeber Dr. Matthias Lange Clemens Krauss Dr. Ulrich Focken

  2. Content • Horizontal exchange of wind power in Germany • Balancing concepts • Wind power predictions (forecasts) • Operative experiences • Conclusions Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  3. TSO TSO Renewable energy act (EEG) - delivery of renewable energy to customers Distribution Network EEG-energy is passed on from the producers to the final customers. Payment (feed in tariffs) are passed on as well. EEG-Quota Sales Company EEG Plant (e.g. Wind Park) Final Customer Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  4. Installed capacity in Germany: 18336 MW 7628 MW (42%) 3288 MW (18%) 7164 MW (39%) 256 MW (1%) Transmission System Operators: E.ON Vattenfall EnBW RWE Spatial distribution of wind energy in Germany Installed capacity in Germany: 18336 MWas of 31.01.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  5. Characteristic wind energy production pattern Example: January to March 2004, Germany, hourly values changing levels steep gradients Source: ISET Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  6. E Extrapolation Immediate horizontal exchange between TSOs EONtransmission zone VETTZ2 factors: • Upscaling of production based on measurements at representative wind farms • Exchange of wind power production every 15 min x ARZ2 x ARZ4 x ARZ3 x ARZ1 x ARZ2 x ARZ4 x ARZ3 x ARZ1 The example shows the data signals of only one TSO WERZ1 E E _ + _ _ _ Grid control Grid control from TZi EnBW TZ3 RWE TZ4 x ARZ2 x ARZ4 x ARZ3 x ARZ1 x ARZ2 x ARZ4 x ARZ3 x ARZ1 E E Grid control Grid control Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  7. TSO TSO Balancing of wind energy prediction deviations Balancing power stations Power Market TSO is responsible for converting fluctuating wind energy into baseload (EEG-Quota) Distribution Network EEG-Quota Trader Sales Company EEGplant Final Customer Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  8. Balancing concepts • There are two main approaches for managing differences between prediction and actual production 1. Separate balancing 2. Combined balancing wind power fluctuations wind power fluctuations conventional fluctuations conventional fluctuations e.g. load, power plants • Benefits from short-term predictability and limited gradients • Contracted reserve / intra-day market • High transparency • Benefits from uncorrelated fluctuations • Flexible pool of power plants / trading • Lower additional costs for balancing Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  9. Wind Energy Prediction Systems - Requirements of TSOs Requirements: • Predictions of nationwide wind power production • Required time-horizons: 0 – 96 h (until next working day, power exchange closed at weekends) • High time resolution (hourly or 1/4 hourly) System Providers: • Increased demand due to new EEG (renewable energy act) • Strong competition among providers • Three main system providers with scientific background in Germany Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  10. Wind Energy Prediction System: Previento (energy & meteo systems) as an example Previento • Physical Model: • Spatial refinement • Thermal stratification • Regional upscaling • Forecast uncertainty Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  11. Achievable prediction accuracy • Prediction for all of Germany • Evaluation period Y2005 • Daily operational predictions • Root mean square error (RMSE) normalized to installed capacity RMSE [% inst. capacity] • Expected prediction quality in normal wind years: • 4 – 6 % intra-day (3 to 10 h) • 6 – 8 % day-ahead • 8 – 10 % 2 day-ahead Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  12. Prediction quality of day-ahead forecasts: monthly reporting day-ahead forecast RMSE [% inst. capacity] Significant changes in prediction quality from month to month. Ranking of quality changes as well. Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  13. Measures for reducing balancing costs • Use of several prediction systems • Frequent intra day updates of predictions • Meteorological training for operators • Meteorological hotline • Intra day trading • Explicit consideration of changing wind power uncertainty for power plant dispatch Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  14. Prediction examples (1) Predictions for Thursday, February 9, 2006 - in MW; EnBW Share (13%) Day-ahead forecast Latest (intraday) forecast Black: Actual wind production Blue: Previento Green: System 2 Purple: System 3 Shaded area: planning schedule Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  15. Prediction examples (2) Predictions for Monday, 20. September 2004 Actual wind production Day-aheadprediction (Sunday) Wind production EnBW-quota (13,68%) [MW] Predictions can change significantly from day to day Basis for planning (Friday) hours; September 20, 2004 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  16. Operational experiences:Adjustment of plant dispatch MW [MW] 24.12.2004 25.12.2004 24.12.2004 25.12.2004 MW At the same time: Load forecast for the 25.12.2004 too high -> strong reduction of nuclear power plants necessary 24.12.2004 25.12.2004 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  17. Conclusions • Experiences since September 2004 • 18 GW of wind energy have been integrated successfully • Immediate horizontal exchange is manageable • Flexible park of power plants is advantageous for integrated balancing of fluctuations • Competition between prediction systems increases prediction accuracy • Huge prediction errors still occur in specific weather conditions Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  18. Outlook • Additional wind energy is manageable • But specific balancing costs will increase (wind prediction errors will be higher than errors of other fluctuations) • Wind power will have to participate partly in the balancing task • Wind power predictions have to be improved to reduce huge predictions errors Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

  19. Company Profiles • EnBW Trading GmbH: • Trading division of EnBW AG • Provides balancing services to TSOs • EnBW AG is third largest energy company in Germany • energy & meteo systems GmbH: • Operator of wind power prediction system Previento • provides dispatcher training, meteorological hotline • R&D: e.g. combination of meteorological weather data Talk on Thursday Session DT1: Dr. Ulrich Focken (energy & meteo systems) OPTIMAL COMBINATION OF DIFFERENT NUMERICAL WEATHER PREDICTIONS FOR IMPROVED WIND POWER PREDICTIONS Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems

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