Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 503-509.doi: 10.11896/j.issn.1002-137X.2017.11A.107

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Multi-objective Moth-flame Optimization Algorithm Based Optimal Reactive Power Dispatch for Power System

LI Wei-kun, QUE Bo, WANG Wan-liang and NI Li-zhou   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In view of the increasing power energy demand and the drawback of conventional reactive power optimization methods,how to effectively solve the reactive power optimization has become a hot spot in power research.This paper proposed a multi-objective model of reactive power optimization problems in power system and a multi-objective moth-flame optimization algorithm (MOMFA) to optimize problems with multiple objectives for the first time.A fixed-sized external archive,grid and select mechanism are integrated to the MOMFA for maintaining and improving the pareto optimal solutions.The proposed algorithm is compared with two well-known algorithms on CEC multi-objective optimization test problems.Moreover,the proposed algorithm was simulated in real power system data and compared with two well-known algorithms:multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm version 2(NSGA-II).The results demonstrate that the proposed algorithm is outperforms other algorithms in reactive power optimization.

Key words: Multi-objective optimization,Evolutionary algorithm,Reactive power optimization,Moth-flame,Power system

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