Wind Speed and Power Forecasting Based on RBF Neural Network

摘要：

As a renewable and clean energy source, wind power is being widely utilized all over the world. The uncertainty of wind speed, however, makes certain trouble for the development of wind power generation. In order to relieve the disadvantageous impact of wind speed intermittence on the connected power system, the wind power forecasting needs to be carried out. In this paper, a wind speed and power forecasting method based on RBF neural network is proposed. In which, the influence of the dataset construct method on the forecasting accuracy is researched. The simulation results show that the forecasting accuracy is improved by performing the dataset reconstruction. And it is proved that the higher forecasting accuracy of wind power can be gotten through introducing the wind speed as RBF inputs.

关键词： wind speed wind power forecasting RBF neural network dataset reconstruction

作者: Wu Junli Liu Xingjie Qian Jian

作者单位: Department of Electrical Engineering North China Electric Power University Baoding, China Bayin Wind Farm Longyuan Baotou Wind Power Co.,Ltd.Baotou, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 298-301

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）