Short-term wind speed combined forecasting method for wind turbine cabin of wind power plant

• Main Authors: SUN HONGCHUAN, ZHANG CHEN, PENG LIXIA, CHEN YUN, LIU YUEWEI, DU JIE, LU JINGUI, PAN LINLIN, CAO YIJIA, DAI KAN, LIU YUBAO, MAO DONGYAN
• Format: Patent
• Language: Chinese; English
• Published: 06.07.2016
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a short-term wind speed combined forecasting method for a wind turbine cabin of a wind power plant. The method comprises the steps of analyzing the similarity of wind speed subsequences of a forecasted wind turbine cabin and all wind turbine cabins within a certain time period day by day by adopting a dynamic time warping method and a correlation coefficient method separately, extracting wind speed data of a plurality of subsequences with the most similar evolution, separately establishing a generalized regression neural network sub-model forecasting unit based on the dynamic time warping method and the correlation coefficient method, and globally optimizing specific parameters of each sub-model by adopting a particle swarm optimization, wherein the mean of the forecasting results of the two sub-models is used as a final forecasting result of the combined forecasting method. The method realizes fine forecasting of the cabin wind speed of each wind turbine in the wind power plant, there