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Dr. Ulrich Focken EWEC 2007 MILAN, 08. May 2007 >>> Optimal Combination of different Wind Power Predictions Slide 2 >>> 2 Overview Motivation Weather Models Classification and Combination Summary Slide 3 >>> 3 Motivation Wind power prediction systems commonly use only one single numerical weather prediction model (NWP). But everyday experience shows: NWP models have strengths and weaknesses in different situations. Our approach: Optimal combination of weather models adapted to different weather situations. Slide 4 >>> 4 Combining Europes NWP for a better forecast Slide 5 >>> 5 Domains overlap Slide 6 >>> 6 Previento the physical approach Previento Physical Model: Spatial refinement Thermal stratification Regional upscaling Forecast uncertainty Slide 7 >>> 7 rmse root mean square error (rmse) dayahead- forecast January-October 2005 for single forecasts Slide 8 >>> 8 Rule-based combination is required Combine and average: [...] Simple average performs as well as more sophisticated statistical approaches. Clemen, R.T., Combining forecasts: A review and annotated bibliography, Int. Journal of Forecasting 5 (1989) 559-582. Rule-based forecasting: [...] We believe that this procedure will lead to improvements. Armstrong,J.S., Combining Forecasts: The End of the Beginning or the Beginning of the End?, Int. Journal of Forecasting 5 (1989) 585-588. use weather information as expert input Slide 9 >>> 9 Combination of wind power forecasts combination tool 1. classification of weather situation 2. optimal combination Model 1 + Previento Model 2 + model X + Previento combined wind power prediction Model n + Previento Model 3 etc.... CombiTool Slide 10 >>> 10 How the CombiTool works 1. Classification Find significant weather situations Principal Component Analysis Simplifying the dataset of meteorological parameters by reducing multi-dimensional data set to lower dimensions Clustering Clustering groups similar objects into different subsets (clusters), so that the data in each subset share some common trait. here: similar weather situtation 2. Optimal Combination Find the best combined forecast Find in each situation (cluster) the optimal weighting factors Slide 11 >>> 11 Results Clustering: Mean of u- und v-component and pressure in clusters low passing North high pressure pmsl [mbar] Slide 12 >>> 12 Weather situation Cyclone passing type A Slide 13 >>> 13 Weather situation Cyclone passing type A Slide 14 >>> 14 Cyclone passing type A : one model is delayed power [% inst. power] days Slide 15 >>> 15 High pressure Eastern Europe Slide 16 >>> 16 High pressure Eastern Europe: models differ power [% inst. power] days Slide 17 >>> 17 Combination 18. Juli 2005 (+1d,2d,3d) Slide 18 >>> 18 Combination 9. Januar 2005 (+1d,2d,3d) Slide 19 >>> 19 Optimal factors differ from situation to situation normalized average combination factors [%] Slide 20 >>> 20 Accuracy in individual weather situations using optimal weights for each weather situation leads to considerable improvement best single model rmse [% inst. power] Cyclone passing type A High pressure Eastern Europe sitation based combination 3.9 % overall rmse 5.0 % Slide 21 >>> 21 Combination in extreme events power [% inst. power] days combination combination very benefitial in extreme events Slide 22 >>> 22 Summary NWP have strengths and weaknesses in different weather situations. Just putting together forecasts is not sufficient, careful selection needed. Automatic classification scheme based on methods from synoptic climatology generates useful weather classes. Optimal combination based on weighting factors for specific weather situations outperforms individual forecasts. Combination avoids large forecast errors in extreme events Slide 23 >>> 23 Summary The system will go in operation at in Juli It will use at least 8 forecasts from 4 different forecast provider as input Slide 24 >>> 24 Thanks for your attention ! Slide 25 >>> 25 >>> Contact Dr. Ulrich Focken energy & meteo systems GmbH Marie-Curie Strae 1 26129 Oldenburg ulrich.focken@energymeteo.de www.energymeteo.de