风场短期风速预测研究

提出一种基于支持向量机的短期风速预测模型,并通过小波分解和遗传算法实现模型中的数据预处理和参数寻优。模型包括数据处理单元、参数寻优单元和支持向量机单元,以历史风速值作为输入,输出未来时间段的风速值。同时,通过引入模型的可调参数,提高模型对应不同风场风速数据的普遍适应性。实验结果表明,模型的预测效果良好,并具有较好的适应性,可适应不同地区的风场数据。

Short-Term Wind Speed Forecasting for Wind Farm

A wind speed forecasting model for wind farm based on support vector machine is proposed.Through wavelet decomposition and genetic algorithm,the data are preprocessed and the parameters are optimized.The model includes data processing unit,parameter optimization and support vector machine unit.The historical wind speed data is input to the model,and the model outputs the future wind speed data.Meanwhile,the adjustable parameters of the model is introduced,in order to improve the general adaptability for the different wind speed data.The simulation results show that the forecast wind speed is following the true value,what’s more,the model can adapt to different wind data.