基于小波理论的风电功率实时协同预测研究

Study on Real-time Cooperative Prediction Based on Wavelet Theory for Wind Power

风力发电联网运行是实现风能大规模开发利用的主要途径,准确的风电功率实时预测是实现风能大规模合理调度的有效手段。对风电功率波动特性进行了分析,得到合理的小波分解层数,通过选取各层预测的最优方法,从而得到协同预测模型。最后以吉林省某风场的实测数据为例,阐述了模型选取的准则,预测结果验证了协同预测模型的有效性。

Wind power generation with network running is the main way to realize the exploitation and utiliza- tion of wind energy in large-scale. Accurate real-time prediction of wind power is an effective means to achieve rational management of wind energy in large-scale. This paper analyzes the characteristics of wind power fluctu- ations, then it gets reasonable wavelet decomposition layers, by Selecting optimal prediction method for different frequency components, real-time cooperative prediction model based on wavelet theory for wind power is estab- lished. Finally By means of the measured date of a wind farm in Jilin Province, we expound the criteria of mod- el selection, the prediction results show the effectiveness of the cooperative prediction model.