期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：47
期号：1
页码：313-317
出版社：Journal of Theoretical and Applied
摘要：As wind power is a mature and important renewable energy, wind power capacity forecasting plays an important role in renewable energy generation�s plan, investment and operation. Combined model is an effective load forecasting method; however, how to determine the weights is a hot issue. This paper proposed a combined model with differential evolution optimizing weights. The proposed model can improve the performance of each single forecasting model of regression, BPNN and SVM. In order to prove the effectiveness of the proposed model, an application of the China�s wind power capacity was evaluated from 2000 to 2010. The experiment results show that the proposed model gets the maximum mean absolute percentage error (MAPE) value 1.791%, which is better than the results of regression, BPNN and SVM.
关键词：Capacity Forecasting; Differential Evolution Algorithm; Wind Power
