Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization

被引：0

作者：

Wang, Shouzheng ^{[1
]}

Ma, Lixin ^{[1
]}

Sun, Dashuai ^{[1
]}

机构：

[1] Univ Shanghai Sci & Tech, Dept Elect Engn, Shanghai, Peoples R China

来源：

2010 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2010年

关键词：

reactive power optimization; differential evolution; particle swarm optimization; hybrid differential evolution particle swarm optimization;

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：

Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms'. It is shown that the approach developed is feasible and efficient.

引用

页数：4

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