WIND SPEED FORECASTING BASED ON SUPPORT VECTOR MACHINE WITH FORECASTING ERROR ESTIMATION

摘要：

An approach of a mean hourly wind speed forecasting in wind farm is proposed in this paper.It applies support vector regression as well as forecasting error estimation.Firstly, support vector regression is applied to the mean hourly wind speed forecasting.Secondly, a support vector classifier is trained to estimate the forecasting error.Finally, the forecasting results can tailor themselves to the estimated forecasting error, and thus improve the forecasting precision.To test the approach, three-year data from a wind farm is given as a support vector regression process, and a support vector classifier is trained in addition to estimate the forecasting error.Experimental results show that the proposed approach can achieve higher quality of mean hourly wind speed forecasting; also it has lower mean square error compared with the traditional support vector regression forecasting.

关键词： Wind speed Forecasting Forecasting error estimation Support vector machine Regression

作者: GUO-RUI JI PU HAN YONG-JIE ZHAI

作者单位: School of Energy and Power Engineering, North China Electric Power University, Beijing 102206, China School of Control Science and Engineering, North China Electric Power University, Baoding 071003, Ch

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 2735-2739

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）