A hybrid particle swarm optimisation with social weight for non-convex economic dispatch problem

被引：3

作者：

Guo, Jinglei ^{[1
]}

Wu, Zhijian ^{[2
]}

Zhao, Bin ^{[3
]}

机构：

[1] Cent China Normal Univ, Dept Comp Sci, Wuhan 430079, Peoples R China

[2] Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China

[3] Wuhan Univ Technol, Sch Automat, Wuhan 430079, Peoples R China

来源：

INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY | 2013年 / 46卷 / 03期

基金：

美国国家科学基金会;

关键词：

economic dispatch; particle swam optimisation; social weight factor;

D O I：

10.1504/IJCAT.2013.052802

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents a hybrid particle swarm optimisation with social weight (HSWPSO) to solve the economic dispatch (ED) problem in power system. Due to equality constraints and non-convex characteristics in ED problem, HSWPSO employs social weight factor, extremum disturbance operator and correction operator to overcome difficulties. The social weight factor is used to improve the global and local search ability of the swarm. The extremum disturbance operator helps trapped particles escape from the local optima. The correction operator ensures the position of particle satisfy the power balance equation. HSWPSO algorithm is applied to two kinds of ED problems, namely ED with valve-point effects and ED with multiple fuels. Experiment results show the effectiveness and feasibility of HSWPSO.

引用

页码：252 / 258

页数：7

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