Probabilistic Load Flow using Latin Hypercube Sampling with Dependence for Distribution Networks

被引：0

作者：

Cao, Jun ^{[1
]}

Du, W. ^{[1
]}

Wang, H. F. ^{[1
]}

Xiao, L. Y. ^{[2
]}

机构：

[1] Queens Univ Belfast, Dept Elect Engn, Belfast, Antrim, North Ireland

[2] Chinese Acad Sci, Inst Elect Engn, Beijing, Peoples R China

来源：

2011 2ND IEEE PES INTERNATIONAL CONFERENCE AND EXHIBITION ON INNOVATIVE SMART GRID TECHNOLOGIES (ISGT EUROPE) | 2011年

基金：

英国工程与自然科学研究理事会;

关键词：

Latin Hypercube Sampling; correlation; probabilistic load flow; distribution networks; RADIAL-DISTRIBUTION SYSTEMS; PERFORMANCE;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The paper adopts the Latin Hypercube Sampling with Dependence (LHSD) method to solve the Probabilistic Load Flow (PLF) problem with correlated random variables for distribution networks. The proposed method is investigated using modified IEEE 34 distribution system with random loads, Wind power and Photovoltaics (PVs). Three different cases are studied and the comparison results shows that the LHSD method handles correlations efficiently and presents an accurate simulation result with a much smaller simulation size. The method has the potential to be applied in many power system probabilistic problems.

引用

页数：6

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