可再生能源2017，Vol.35Issue(1)：86-92,7.
基于改进诱导有序加权算子的风电功率预测
Wind power forecasting based on improved induced ordered weighted operator
摘要
Abstract
In order to overcome the inaccuracy of the ultra-short-term wind generation forecast,this paper proposed a combination forecasting method,which based on the combination of Theil coefficient and induced ordered weighted operator.Due to the actual wind power outputs are unknown during the forecasting,this method may not be directly utilized.To solve the problem of the unknown induction value,a novel method has been proposed to improve the induced ordered weighted operator,which derives the threshold induced value of wind outputs from the average precision of the first couple of moments in each single forecast model.Then,the error information matrix based algorithm are introduced to analyze the redundancy of individual prediction methods,and optimize the single forecast model.Finally,a combination forecast models are developed,on the basis of the Theil coefficient along with three kinds of improvement of the induced ordered weighted operator.Both theoretical analysis and experimental results are also provided to validate that the combined model.With the deployment of combination of the Theil coefficient and the induced ordered weighted arithmetic average operator(IOWA),the accuracy of wind power forecast is effectively improved.关键词
Theil不等系数/诱导有序加权算子/风电功率/超短期预测/组合预测Key words
theil coefficient/induced ordered weighted operator/wind power/ultra-short-term prediction/combination forecast分类
能源科技引用本文复制引用
何亚,李坚,张真源,梁浩,黄琦..基于改进诱导有序加权算子的风电功率预测[J].可再生能源,2017,35(1):86-92,7.基金项目
国家自然科学基金项目(61503063,51277022) （61503063,51277022）
四川省科技计划项目(2016GZ0143,2016GFW0170). （2016GZ0143,2016GFW0170）
