可再生能源2017，Vol.35Issue(9)：1324-1330,7.
基于集对分析聚类法的超短期风电功率区间预测
Ultra short term wind power interval prediction with set pair analysis in cluster analysis
摘要
Abstract
High-precision wind power prediction is an important means to ensure the safe and economical operation of wind power system with high permeability. Now the point prediction method is various, prediction accuracy is difficult to improve, so in this paper we presents a method for wind power interval prediction based on the set pair analysis theory with the ARIMA algorithm. Firstly, combined with K-means clustering algorithm, the clustering evaluation function is established and get wind power clustering results; Establish the relationship between the wind power and influence factors;For a new wind power data, calculate the distance with each class and find the cluster's upper limit and lower limit. According to the range of the error distribution, adjust the wind power interval and can get the final interval prediction result.Compare the method with confidence interval method, and introduce three evaluation index model, the effectiveness of the wind power interval prediction based on the set pair analysis theory is verified.关键词
风电功率/区间预测/集对分析/聚类分析Key words
wind power/interval prediction/set pair analysis/cluster analysis分类
能源科技引用本文复制引用
杨茂,都键,李大勇,孙涌,贾云彭..基于集对分析聚类法的超短期风电功率区间预测[J].可再生能源,2017,35(9):1324-1330,7.基金项目
国家自然科学基金项目(51307017) （51307017）
吉林省产业技术与专项开发项目(2014Y124). （2014Y124）
