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浙江大学学报(工学版)
J4  2011, Vol. 45 Issue (3): 510-514    DOI: 10.3785/j.issn.1008-973X.2011.03.018
    
Optimal allocation of short circuit current limiting strategies base on
modified discrete particle swarm optimization algorithm
CHEN Li-li, HUANG Min-xiang, GAN De-qiang
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  

The conventional particle swarm optimization algorithm (PSO) was improved and a modified discrete particle swarm optimization algorithm (MDPSO) was proposed to solve the problem of the optimal allocation of short circuit current limiting strategies in actual power system. The particles were coded in binary and decimal system and a zero operator was used to optimize the initial population. A single-bit mutation operator was introduced to prevent the algorithm from falling into a local optimal solution. The feasibility of the MDPSO method was verified and compared with the genetic algorithm (GA) and the ordinary discrete particle swarm optimization algorithm (DPSO) by the simulation  of the New England 39-bus system and the 82-bus system in western China.

Published: 16 March 2012
CLC:  TM 73  
  TM 471  
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Cite this article:

CHEN Li-li, HUANG Min-xiang, GAN De-qiang. Optimal allocation of short circuit current limiting strategies base on
modified discrete particle swarm optimization algorithm. J4, 2011, 45(3): 510-514.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2011.03.018     OR     http://www.zjujournals.com/eng/Y2011/V45/I3/510


基于改进离散粒子群算法的限流措施优化配置

为求解实际电力系统中的限流措施优化配置问题,对传统粒子群算法（PSO）进行改进,提出一种改进离散粒子群算法（MDPSO）.此MDPSO算法采用二进制结合十进制的编码方式,并引入置0算子,优化初始种群,同时引入单方向的变异算子,防止算法陷入局部优化解.应用此算法对新英格兰39节点系统和中国西部82节点系统进行限流措施优化配置计算,并同遗传算法（GA）和普通离散粒子群算法（DPSO）进行比较,仿真结果表明,MDPSO算法是有效可行的.

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