Robust Optimal Operation of Active Distribution Network Based on Minimum Confidence Interval of Distributed Energy Beta Distribution

作     者：Yanhong Luo Qiubo Nie Dongsheng Yang Bowen Zhou Yanhong Luo;Qiubo Nie;Dongsheng Yang;Bowen Zhou

作者机构：the Department of Electric EngineeringNortheastern UniversityShenyang 110004China 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2021年第9卷第2期

页      面：423-430页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：supported in part by the National Natural Science Foundation of China(No.61703081) the Liaoning Joint Fund of National Natural Science Foundation of China(No.U1908217) the Natural Science Foundation of Liaoning Province(No.20170520113) the Fundamental Research Funds for the Central Universities(No.N2004016) 

主　　题：Active distribution network robust optimization Beta distribution second-order cone 

摘      要：With the gradual increase of distributed energy penetration,the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution *** order to deal with the inevitable uncertainty of distributed energy,a new robust optimal operation method is proposed for active distribution network(ADN)based on the minimum confidence interval of distributed energy Beta distribution in this ***,an ADN model is established with second-order cone to include the energy storage device,capacitor bank,static var compensator,on-load tap changer,wind turbine and ***,the historical data of related distributed energy are analyzed and described by the probability density function,and the minimum confidence interval is obtained by interval ***,via taking this minimum confidence interval as the uncertain interval,a less conservative two-stage robust optimization model is established and solved for *** simulation results for the IEEE33-bus distribution network have verified that the proposed method can realize a more stable and efficient operation of the distribution network compared with the traditional robust optimization method.