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Short-Term Wind Speed Forecasting of Wind Farm Based on Least Square-Support Vector Machine

DU Ying1,LU Ji-ping1,LI Qing2,DENG Ying-ling3 (1.State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University),Shapingba District,Chongqing 400044,China;2.Gansu Clean Source of Wind Power Co., Ltd., Lanzhou 730050,Gansu Province,China;3.China CIVIL Zhanjiang Air Traffic Management Station, Zhanjiang 524017,Guangdong Province,China)  
A wind speed forecasting for wind farm based on least squares support vector machine (LS-SVM) is proposed. Taking historical wind speed data, atmospheric pressure and temperature as the input, the wind speed and environmental condition are trained by LS-SVM, then a forecasting model is built, and by use of grid search the parameters of the model are determined. Forecasting wind speed by the proposed method, the obtained results are basically in accordance with the values of actual wind speed. Comparing the wind speeds forecasted by the proposed method with those forecasted by BP neural network based method, it is shown that the proposed method is better than the latter in robustness and forecasting accuracy.
【Fund】: 国家重点基础研究发展计划项目(973项目)(2004CB217908)。~~
【CateGory Index】: TP183;TM614
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