Adaptive Ultra-short-term Wind Power Prediction Based on Risk Assessment  

作　　者：Yusheng Xue Chen Yu Kang Li Fushuan Wen Yi Ding Qiuwei Wu Guangya Yang 

机构地区：[1]State Grid Electric Power Research Institute/NARI Group Corporation,Nanjing 211000,China [2]Queen’s University Belfast,Northern Ireland,BT95AH,UK [3]College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China [4]Technical University of Denmark,Lyngby 2800,Denmark

出　　处：《CSEE Journal of Power and Energy Systems》2016年第3期59-64,共6页中国电机工程学会电力与能源系统学报（英文）

基　　金：supported in part by Special Fund of the National Basic Research Program of China(2013CB228204);NSFCNRCT Collaborative Project(No.51561145011);Australian Research Council Project(DP120101345);State Grid Corporation of China.

摘　　要：A risk assessment based adaptive ultra-short-term wind power prediction(USTWPP)method is proposed in this paper.In this method,features are first extracted from the historical data,and then each wind power time series(WPTS)is split into several subsets defined by their stationary patterns.A WPTS that does not match any of the stationary patterns is then included in a subset of non-stationary patterns.Each WPTS subset is then related to a USTWPP model that is specially selected and optimized offline based on the proposed risk assessment index.For online applications,the pattern of the last short WPTS is first recognized,and the relevant prediction model is then applied for USTWPP.Experimental results confirm the efficacy of the proposed method.

关 键 词：Error evaluation offline optimization online matching positive error vs negative error risk index time series features wind power prediction 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]