Wind Speed Prediction Based on EEMD Analysis and AR Modeling
HE Qun,ZHAO Wen-shuang,JIANG Guo-qian,XIE Ping
Institute of Electrical Engineering, Yanshan University, Measurement Technology and Instrumentation Key Lab of Hebei Province, Qinhuangdao, Hebei 066004, China
Abstract：Aiming at the non-stationary and nonlinear of wind speed sequences ,an integrated method based on EEMD and AR modeling is proposed. The wind speed time series are firstly pretreated by EEMD and decomposed into a series of relatively smooth IMF components, highlighting the local characteristics of the original sequences. Then each IMF component is modeled and forecasted using AR modeling, thus reducing the difficulty of modeling and forecast costs. Eventually, the prediction results of each component are taken for integration by the least square method to get the right values. A set of wind speed data from some wind farm are verified and the results show that compared with the single AR modeling prediction and forecast based on EMD and AR integration, the proposed method can effectively improve the prediction accuracy.
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2015, Vol. 36 
