An Operational Application of NWP Models in a Wind Power Forecasting Demonstration Experiment

Author:

Yu Wei1,Plante André2,Dyck Sarah1,Chardon Laurent1,Forcione Alain3,Choisnard Julien4,Benoit Robert1,Glazer Anna1,Roberge Gaétan3,Petrucci Franco2,Bourret Jacques4,Antic Slavica4

Affiliation:

1. Atmospheric Numerical Prediction Research Section (RPN-A), Meteorological Research Division (MRD), Environment Canada (EC), 2121 TransCanada Highway, #500, Dorval (QC), H9P 1J3, Canada

2. Meteorological Service of Canada (MSC), Environment Canada, 2121 TransCanada Highway, #400, Dorval (QC), H9P 1J3, Canada

3. Institut de Recherche d'Hydro-Québec (IREQ), Hydro-Québec (HQ), 1800, boul. Lionel-Boulet, Varennes, J3X 1S1 Canada

4. Hydro-Québec Distribution (HQD), Hydro-Québec (HQ), 75 Boulevard René-Lévesque Ouest, Montreal, H2Z 1A4, Canada

Abstract

Environment Canada (EC) and Hydro-Québec (HQ) have been collaborating in a Research & Development and Demonstration project on a high resolution wind energy dedicated forecasting system (SPÉO: Système de Prévision ÉOlien under its French acronym). This project emphasizes the operational tests and the forecast of high impact events, e.g. wind ramps. It was found that SPÉO improves the Canadian Regional Deterministic Prediction System (RDPS), by about 18% in terms of the RMSE (Root Mean Square Error) of the predicted wind speed when compared with mast observations from three wind power plants. The improvement is most significant in the cold season. When the average wind speed measured at all wind turbines (nacelle anemometer) is used as a reference, SPÉO improves the RMSE of the average wind speed at a wind power plant in complex terrain (24%) compared with that of RDPS. However, there is almost no improvement for two other wind power plants located in less complex terrain. The average wind speed is corrected with the average wind speed measured at all turbines, and is then fed into a wind-to-power conversion module for power production forecasts. The power production forecast is improved by 6% on average in complex terrain when SPÉO winds are used as input compared to the RDPS. The most important finding of this project is SPÉO's ability to predict ramps due to mountain waves/downslope winds. The proposed forecast index for ramps based on the Froude number is useful for predicting the onset of this kind of ramp when a high resolution NWP model is unavailable.

Publisher

SAGE Publications

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

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