An Adaptive Particle Swarm Optimization Algorithm for Reactive Power Optimization in Power System

被引：3

作者：

Wu, Enqi ^{[1
]}

Huang, Yue ^{[2
]}

Li, Dan ^{[3
]}

机构：

[1] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding 071003, Peoples R China

[2] Shenyang Ligong Univ, Sch Informat Sci & Engn, Shenyang 110168, Peoples R China

[3] Northeast China Grid Co Ltd, Shenyang 110181, Peoples R China

来源：

2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2010年

关键词：

particle swarm optimization; adaptive mutation; reactive power optimization; DISPATCH;

D O I：

10.1109/WCICA.2010.5553988

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An adaptive particle swarm optimization(APSO) algorithm is presented to solve the problem that the standard particle swarm optimization(PSO) algorithm is easy to fall into a locally optimized point, where inertia weight is nonlinearly adjusted by using population diversity information. Velocity mutation factor and position interchange factor are both introduced. The APSO algorithm thus improves its solvability for global optimization to avoid effectively the precocious convergence. The new algorithm is applied to reactive power optimization of the standard IEEE-30-bus power system as instances, and the simulation results show the effectiveness and feasibility of APSO algorithm for the reactive power optimization. It is proved to be efficient and practical during the reactive power optimization.

引用

页码：3132 / 3137

页数：6

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