基于非参数估计和最优Copula的电力系统概率潮流算法

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英文篇名：Probability Trend Algorithm for the Electric Power System Based on Non-parametric Estimation and Optimal Copula 作者：李权 ; 王鑫 ; 郎永波 ; 王昕 英文作者：Li Quan;Wang Xin;Lang Yongbo;Wang Xin;College of Electrical Engineering, Shanghai University of Electric Power;Yanbian Power Supply Co., State Grid Jilin Electric Power Co., Ltd.;Center of Electrical & Electronic Technology, Shanghai Jiao Tong University; 关键词：风电系统 ; 概率潮流 ; 相关性 ; 非参数估计 ; 最优Copula 英文关键词：wind power system;;probability trend;;correlation;;non-parametric estimation;;optimal Copula 中文刊名：DQZD 英文刊名：Electrical Automation 机构：上海电力学院电气工程学院;国网吉林省电力有限公司延边供电公司;上海交通大学电工与电子技术中心; 出版日期：2019-05-30 出版单位：电气自动化 年：2019 期：v.41;No.243 基金：国家自然科学基金项目(61673268) 语种：中文; 页：DQZD201903027 页数：4 CN：03 ISSN：31-1376/TM 分类号：92-95

摘要

分布式发电的接入给电力网络带来了极大的不确定性,概率潮流计算是分析这种不确定性的重要方法。针对变量边缘分布求解以及多个节点存在相关性的问题,提出了一种基于非参数估计和最优Copula的电力系统概率潮流算法。利用非参数估计构建了随机变量的边缘分布,采用Copula函数描述随机变量间的相关性,并基于极大似然估计和欧氏距离法确立了最优Copula函数,从而获得了随机变量的联合概率分布,最后对联合分布进行随机采样计算。经IEEE 30节点系统仿真,结果表明经过非参数估计后的风速边缘分布符合风速频率直方图的分布规律,同时算法精度可靠,适合计算含分布式发电接入的网络潮流。
        The access of distributed generation causes great uncertainty to the power network, and probability trend calculation is an important method for analyzing this uncertainty. With regards to solution of marginal distribution of variables as well as correlation among multiple nodes,this paper presented a probability trend algorithm for the electric power system, based on non-parametric estimation and optimal Copula. Non-parametric estimation was used to construct marginal distribution of random variables, Copula function was adopted to describe correlation among random variables, and optimal Copula function was established on the basis of maximum likelihood estimation and Euclidean distance method, so that a joint probability distribution of random variables was obtained. Finally, joint distribution was calculated by random sampling. Results of IEEE 30-node system simulation showed that the marginal distribution of wind speed after non-parametric estimation was consistent with the distribution regularity of wind speed frequency histogram, and that the algorithm had a reliable accuracy and was suitable for the calculation of the network trend with access of distributed power generation.

引文

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