Random Spanning Tree Based Improved GA for Distribution Network Reconfiguration

被引：0

作者：

Quyang, Wu ^{[1
]}

Cheng, Haozhong ^{[1
]}

Zhang, Xiubin ^{[1
]}

Yao, Liangzhong ^{[2
]}

Bazargan, Masoud ^{[2
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200030, Peoples R China

[2] AREVA T&D, Technol Ctr, Stafford ST17 4LX, England

来源：

2009 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), VOLS 1-7 | 2009年

关键词：

Genetic algorithm; distribution network reconfiguration; spanning tree; mutation rate; DISTRIBUTION-SYSTEMS; FEEDER RECONFIGURATION; GENETIC ALGORITHM; LOSS REDUCTION;

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：

Using traditional Genetic Algorithm (GA) to solve distribution network reconfiguration, the required radial network structure can not be ensured and a large number of infeasible solutions are brought about. Although some improved methods were put forward, they either are of computational complexity or can not completely settle the problem. In this paper, the strategy of searching randomly spanning trees is introduced to form an improved GA. The method proposed in this paper is simple and convenient to solve distribution network reconfiguration. Combined with graph theory, this algorithm can ensure any reconfiguration scheme characterized with radial structure of network. Numerical tests on both 33-bus and 69-bus networks show effectiveness and advantage of the proposed algorithm.

引用

页码：1900 / +

页数：2

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