Wind Power Forecasting Based on the BP Neural Network

摘要：

　　Accurate short-term wind power forecasting has important significance to safety,stability and economy of power system dispatching and also it is a difficult problem in practical engineering application.In this paper,by use of the data of numerical weather forecast,such as wind speed,wind direction,temperature,relative humidity and pressure of atmosphere,a short-term wind power forecasting system based on BP neural network has been developed.For verifying the feasibility of the system,some experiments have been were carried out.The results show that the system is capable of predicting accurately the wind power of future 24 hours and the forecasting accuracy of 85.6% is obtained.The work of this paper has important engineering directive significance to the similar wind power forecasting system.

关键词： wind power BP neural network short-term forecast

作者: Jiandong Mao Xiaojing Zhang Juan Li

作者单位: School of Electrical and Information Engineering,Beifang University of Nationalities,North Wenchang Yike solar energy generation limited corporation,Ningxia power generation group,Xinchang Road,Yinchu School of design and art,Beifang University of Nationalities,North Wenchang Road,Yinchuan,750021,Chi

会议类型: 国际会议

会议名称: 2013 International Conference on Energy Research and Power Engineering(2013能源研究与电力工程国际会议)(ERPE2013)

会议地点: 郑州

会议语种:英文

页码: 1-5

在线出版日期: 2013-05-24（万方平台首次上网日期，不代表论文的发表时间）