电力系统保护与控制2016，Vol.44Issue(13)：130-136,7.DOI:10.7667/PSPC151311
基于波动过程聚类的风电功率预测极大误差估计方法
An estimation method for wind power prediction great error based on clustering fluctuation process
摘要
Abstract
Estimating the great error in wind power prediction contributes to optimizing scheduling of power system which contains wind power and improving the ability of the power grid to accommodate large-scale wind power plant. According to the analysis of the error distribution of historical wind power prediction, an approach to estimating the great errorbased on clustering wind power fluctuation process is proposed. Firstly, wind power prediction data is divided into diverse fluctuation processes by swinging door algorithm, and on this basis, cluster prediction errors ofthe same distribution by analyzing the correlation between the fluctuation and the amplitude of wind power and the distribution of prediction errors. Thenthis paperfits probability density distribution of the prediction errors and estimates the great error adopting slide bandwidth kernel density estimation method. Finally,the wind powerdata of BPA in the United Statesis takenas example, the effectiveness of this method is validated by comprehensively analyzing different methods.关键词
风电功率预测/极大误差估计/波动过程聚类/摇摆窗算法/核密度拟合Key words
wind power prediction/great error estimation/fluctuation process clustering/swinging door algorithm/kernel density estimation引用本文复制引用
黄坡,朱小帆,查晓明,秦亮..基于波动过程聚类的风电功率预测极大误差估计方法[J].电力系统保护与控制,2016,44(13):130-136,7.基金项目
国家自然科学基金项目(51207115) （51207115）
