基于空间变换的含风电场和电动汽车配电网概率潮流计算

doi:10.12028/j.issn.2095-4239.2016.0075

储能科学与技术 ›› 2017, Vol. 6 ›› Issue (1): 127-134.doi: 10.12028/j.issn.2095-4239.2016.0075

基于空间变换的含风电场和电动汽车配电网概率潮流计算

朱张涛1，陈豪杰2，戴俊杰1，李卫彬1，李雪2

1国网上海市电力公司长兴供电公司，上海 201913；2上海大学自动化系，上海市电站自动化技术重点实验室，上海 200072

收稿日期:2016-09-27 修回日期:2016-12-01 出版日期:2017-01-03 发布日期:2017-01-03
通讯作者: 李雪，副教授，主要研究方向为电力系统优化，E-mail：lixue@shu.edu.cn。
作者简介:朱张涛（1988—），男，硕士研究生，助理工程师，研究方向为电力系统潮流分析，E-mail：zzt880115@163.com；
基金资助:
国家自然科学基金（61533010）及上海市自然科学基金项目（14ZR1415300）。

Probabilistic load flow calculation of distribution network with wind power and electric vehicles based on space transform#br#

ZHU Zhangtao1, CHEN Haojie2, DAI Junjie1, LI Weibin1, LI Xue2

1Changxing Power Supply Company, SMEPC, Shanghai 201913, China; 2Department of Automation, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai 200072, China

Received:2016-09-27 Revised:2016-12-01 Online:2017-01-03 Published:2017-01-03

摘要/Abstract

摘要： 电动汽车和分布式发电的广泛接入增加了现代配电网的复杂性，同时输入随机变量的相关性对配电网的影响也越来越大。基于此，本文采用Nataf变换或者三阶多项式正态变换实现变量从相关非正态空间到相关标准正态空间的转换，采用初等变换或者正交变换实现变量从相关标准正态空间到独立标准正态空间的转换，从而得到标准的点估计运算所需的相互独立输入随机变量，进而建立了能用2m+1点估计方法求解的概率潮流模型，从而解决了相关输入随机变量的概率潮流问题，以实现含电动汽车的有源配电网系统的仿真运行分析。最后，在一个含风电和电动汽车的IEEE-33节点配电网中进行算例仿真，比较四个方案处理输入随机变量相关性的有效性。算例分析表明，Nataf变换结合初等变换具有最好的精度。

关键词: 电动汽车, 风电场, 配电网, 相关性, 点估计, 概率潮流计算

Abstract: The use of electric vehicles and distributed generation increases the complexity of modern distribution network. This is made more serious with more correlated input of random variables. In this study, we use the Nataf transformation, also called the third order polynomial normal transformations, to transform random variables from a correlated non-normal random vector space (CNNRVS) to a correlated standard normal random vector space (CSNRVS), and use the elementary transformation, also called the orthogonal transformation, to transform random variables from CSNRVS to independent standard normal random vector space (ISNRVS). These lead to the random independent input variables to execute the probabilistic load flow calculations using a 2m+1 point estimate method. Examples was made to simulate an IEEE-33 distribution network with wind power and electric vehicles. Comparison was made between four cases for the correlation among random input variables. The results showed that the Nataf transformation combined with elementary transformation gave the best accuracy.

Key words: electric vehicles, wind farm, distribution network, correlation, point estimate method, probabilistic load flow calculation

朱张涛1，陈豪杰2，戴俊杰1，李卫彬1，李雪2. 基于空间变换的含风电场和电动汽车配电网概率潮流计算[J]. 储能科学与技术, 2017, 6(1): 127-134.

ZHU Zhangtao1, CHEN Haojie2, DAI Junjie1, LI Weibin1, LI Xue2 . Probabilistic load flow calculation of distribution network with wind power and electric vehicles based on space transform#br#[J]. Energy Storage Science and Technology, 2017, 6(1): 127-134.

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基于空间变换的含风电场和电动汽车配电网概率潮流计算

Probabilistic load flow calculation of distribution network with wind power and electric vehicles based on space transform#br#

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