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A physical approach of the short-term wind power prediction based on CFD pre-calculated flow fields 被引量:5

A physical approach of the short-term wind power prediction based on CFD pre-calculated flow fields
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摘要 A physical approach of the wind power prediction based on the CFD pre-calculated flow fields is proposed in this paper. The flow fields are obtained based on a steady CFD model with the discrete inflow wind conditions as the boundary conditions, and a database is established containing the important parameters including the inflow wind conditions, the flow fields and the corresponding wind power for each wind turbine. The power is predicted via the database by taking the Numerical Weather Prediction (NWP) wind as the input data. In order to evaluate the approach, the short-term wind power prediction for an actual wind farm is conducted as an example during the period of the year 2010. Compared with the measured power, the predicted results enjoy a high accuracy with the annual Root Mean Square Error (RMSE) of 15.2% and the annual MAE of 10.80%. A good performance is shown in predicting the wind power's changing trend. This approach is independent of the historical data and can be widely used for all kinds of wind farms including the newly-built wind farms. At the same time, it does not take much computation time while it captures the local air flows more precisely by the CFD model. So it is especially practical for engineering projects. A physical approach of the wind power prediction based on the CFD pre-calculated flow fields is proposed in this paper. The flow fields are obtained based on a steady CFD model with the discrete inflow wind conditions as the boundary conditions, and a database is established containing the important parameters including the inflow wind conditions, the flow fields and the corresponding wind power for each wind turbine. The power is predicted via the database by taking the Numerical Weather Prediction (NWP) wind as the input data. In order to evaluate the approach, the short-term wind power prediction for an actual wind farm is conducted as an example during the period of the year 2010. Compared with the measured power, the predicted results enjoy a high accuracy with the annual Root Mean Square Error (RMSE) of 15.2% and the annual MAE of 10.80%. A good performance is shown in predicting the wind power's changing trend. This approach is independent of the historical data and can be widely used for all kinds of wind farms including the newly-built wind farms. At the same time, it does not take much computation time while it captures the local air flows more precisely by the CFD model. So it is especially practical for engineering projects.
出处 《Journal of Hydrodynamics》 SCIE EI CSCD 2013年第1期56-61,共6页 水动力学研究与进展B辑(英文版)
基金 Project supported by the National Natural Science Foundation of China(Grant No. 51206051)
关键词 short-term wind power prediction physical approach CFD model flow field DATABASE short-term wind power prediction, physical approach, CFD model, flow field, database
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