Reactive Power Dispatch Based on Self-Adaptive Differential Evolution Hybrid Particle Swarm Optimization

被引：0

作者：

Wang, C. ^{[1
]}

Liu, Y. C. ^{[1
]}

Guo, H. H. ^{[1
]}

Chen, Y. ^{[1
]}

机构：

[1] Dalian Maritime Univ, Marine Engn Coll, Dalian, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL APPLICATIONS (CISIA 2015) | 2015年 / 18卷

关键词：

reactive power dispatch; particle swarm optimization (PSO); self-adapting hybrid strategy; global optimization; differential Evolution (DE); FLOW;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Reactive power dispatch, which may have many local optima, is an important and challenging task in the operation and control of electric power system. This paper presents a Self-adaptive Differential Evolution hybrid Particle Swarm (SaDEPS) optimization algorithm for optimal reactive power dispatch problem. In this method, each particle is updated by a randomly selected strategy from a candidate pool, which contains strategies with different searching behaviors. SaDEPS applied to optimal reactive power dispatch is evaluated on IEEE 14-bus system. The numerical results, show that SaDEPS could find high-quality solutions with higher convergence speed and probability.

引用

页码：75 / 78

页数：4

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