A Combination Method for Wind Power Prediction Based on Cooperative Game Theory

作     者：Li Kangping Gao Yajing 

作者机构：North China Electric Power University 

出 版 物：《Electricity》 (电气（英文版）)

年 卷 期：2014年第25卷第2期

页      面：36-40页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0807[工学-动力工程及工程热物理] 

主　　题：wind power combination forecasting cooperative game theory 

摘      要：Accurate prediction of wind power is significant for power system dispatching as well as safe and stable operation. By means of BP neural network, radial basis function neural network and support vector machine, a new combined method of wind power prediction based on cooperative game theory is proposed. In the method, every single forecasting model is regarded as a member of the cooperative games, and the sum of square error of combination forecasting is taken as the result of cooperation. The result is divided among the members according to Shapley values, and then weights of combination forecasting can be obtained. Application results in an actual wind farm show that the proposed method can effectively improve prediction precision.