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Distribution network reactive power optimization based on ant colony optimization and differential evolution algorithm

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3 Author(s)
Yulin, Zhao ; Electric Engineering Department of Northeast Agricultural University, No.59 Mucai Street Xiangfang District Harbin, China ; Qian, Yu ; Chunguang, Zhao

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 reinitialization 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.

Published in:

Power Electronics for Distributed Generation Systems (PEDG), 2010 2nd IEEE International Symposium on

Date of Conference:

16-18 June 2010

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