Distribution Network Reactive Power Optimization Based on Ant Colony Optimization and Differential Evolution Algorithm

被引：0
|
作者：
Zhao Yulin [1 ]
Yu Qian [1 ]
Zhao Chunguang [2 ]
机构：
[1] Northeast Agr Univ, Dept Elect Engn, 59 Mucai St, Harbin, Xiangfang, Peoples R China
[2] Harbin Elect Power Bur, Harbin 150001, Peoples R China
来源：
IEEE PEDG 2010: THE 2ND INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS | 2010年
关键词：
Ant colony optimization; distribution network; differential evolution; reactive power optimization;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Due to the inherent complexity, traditional ant colony optimization (ACO) algorithm is inadequate and insufficient to the reactive power optimization for distribution network. Therefore, firstly the ACO algorithm is improved in two aspects: pheromone mutation and re-initialization strategy. Then the thought of DE is proposed to be merged into ACO, and by producing new individuals with random deviation disturbance of DE, pheromone quantity left by ants is disturbed appropriately, to search the optimal path, by which the ability of search having been improved. The proposed algorithm is tested on IEEE30-bus system and actual distribution network, and the reactive power optimization results are calculated to verify the feasibility and effectiveness of the improved algorithm.
引用
收藏
页码：472 / 476
页数：5
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