1. Energie braucht Impulse 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 GraeberDr. Matthias Lange Clemens KraussDr. Ulrich Focken

2. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems2 Content › Horizontal exchange of wind power in Germany › Balancing concepts › Wind power predictions (forecasts) › Operative experiences › Conclusions

3. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems3 Renewable energy act (EEG) - delivery of renewable energy to customers TSO Distribution Network EEG Plant (e.g. Wind Park) Sales Company Final Customer EEG-Quota TSO EEG-energy is passed on from the producers to the final customers. Payment (feed in tariffs) are passed on as well.

4. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems4 Spatial distribution of wind energy in Germany 7164 MW (39%) 256 MW (1%) 3288 MW (18%) 7628 MW (42%) Transmission System Operators: E.ON Vattenfall EnBW RWE Installed capacity in Germany: 18336 MW Installed capacity in Germany: 18336 MW as of 31.01.2006

5. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems5 Characteristic wind energy production pattern Source: ISET Example: January to March 2004, Germany, hourly values changing levels steep gradients

6. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems6 Immediate horizontal exchange between TSOs E Extrapolation The example shows the data signals of only one TSO EON transmission zone EnBW TZ3 VET TZ2 RWE TZ4 WE RZ1 x A RZ2 x A RZ4 x A RZ3 x A RZ1 + _ Grid control from TZi E E E E x A RZ2 x A RZ4 x A RZ3 x A RZ1 x A RZ2 x A RZ4 x A RZ3 x A RZ1 x A RZ2 x A RZ4 x A RZ3 x A RZ1 _ _ _ factors: Grid control › Upscaling of production based on measurements at representative wind farms › Exchange of wind power production every 15 min

7. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems7 Balancing of wind energy prediction deviations TSO Distribution Network EEG plant Trader Sales Company EEG-Quota TSO Power Market Balancing power stations Final Customer TSO is responsible for converting fluctuating wind energy into baseload (EEG-Quota)

8. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems8 Balancing concepts › There are two main approaches for managing differences between prediction and actual production wind power fluctuations conventional fluctuations e.g. load, power plants 1. Separate balancing › 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 2. Combined balancing conventional fluctuations wind power fluctuations

9. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems9 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

10. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems10 Wind Energy Prediction System: Previento (energy & meteo systems) as an example Previento Physical Model: Spatial refinement Thermal stratification Regional upscaling Forecast uncertainty

11. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems11 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

12. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems12 Prediction quality of day-ahead forecasts: monthly reporting RMSE [% inst. capacity] day-ahead forecast Significant changes in prediction quality from month to month. Ranking of quality changes as well.

13. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems13 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

14. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems14 Prediction examples (1) Day-ahead forecastLatest (intraday) forecast Black: Actual wind production Blue: Previento Green: System 2 Purple: System 3 Shaded area: planning schedule Predictions for Thursday, February 9, 2006 - in MW; EnBW Share (13%)

15. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems15 Prediction examples (2) Predictions for Monday, 20. September 2004 hours; September 20, 2004 Wind production EnBW-quota (13,68%) [MW] Basis for planning (Friday) Day-ahead prediction (Sunday) Actual wind production Predictions can change significantly from day to day

16. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems16 Operational experiences: Adjustment of plant dispatch 24.12.200425.12.2004 [MW] MW 24.12.200425.12.2004 At the same time: Load forecast for the 25.12.2004 too high -> strong reduction of nuclear power plants necessary 24.12.200425.12.2004 MW

17. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems17 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

18. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems18 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

19. 28.02.2006Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems19 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