中国电机工程学报2012，Vol.32Issue(1)：24-31,8.
风电场短期风速的多变量局域预测法
Multivariate Local Prediction Method for Short-term Wind Speed of Wind Farm
摘要
Abstract
Most statistics prediction methods for short-term wind speed are based on univariate wind speed time series, they have limited prediction accuracy; however there is no specific method for selecting variables of multivariate prediction. This paper presented a multivariate local predictor for short-term wind speed prediction of wind farm. It sifted multivariate time series by correlation principle to reconstruct multivariate phase space, and searched the neighborhood of the prediction state points to build the support vector regression models. The data of real-world collected from a wind farm was applied to verify the conclusions. The example results show that the proposed method can improve the searching efficiency of local predictor that can find much more similar neighbor points. And combining with support vector regression （SVR） model that could provide good capability of nonlinear fitness, it can effectively improve the accuracy of short-term wind speed prediction.关键词
风速预测/局域预测/相关系数/支持向量回归/相空间重构Key words
wind speed prediction/local predictor/correlation coefficient/support vector regression/phase space reconstruction分类
信息技术与安全科学引用本文复制引用
郭创新,王扬,沈勇,王媚,曹一家..风电场短期风速的多变量局域预测法[J].中国电机工程学报,2012,32(1):24-31,8.基金项目
新世纪优秀人才支持计划项目(NCET-07-0745) （NCET-07-0745）
浙江省自然科学基金项目(R107062) （R107062）
国家863高技术基金项(2008AA052210) （2008AA052210）
高等学校博士学科点专项科研基金资助项目(20090101110058). （20090101110058）
