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《Proceedings of the Csee》 2005-05
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A MULTI-AGENT PARTICLE SWARM OPTIMIZATION ALGORITHM FOR REACTIVE POWER OPTIMIZATION

ZHAO Bo, CAO Yi-jia (College of Electrical Engineering,Zhejiang University,Hangzhou 310027,Zhejiang Province, China)  
A novel multi-agent particle swarm optimization algorithm (MAPSO) is proposed for optimal reactive power dispatch and voltage control of power system. The method integrates multi-agent system (MAS) and particle swarm optimization algorithm (PSO). An agent in MAPSO represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to decrease fitness value quickly, agents compete and cooperate with their neighbors, and they can also use knowledge. Making use of these agent-agent interactions and evolution mechanism of PSO, MAPSO realizes the purpose of minimizing the value of objective function. MAPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. It is shown that the proposed approach converges to better solutions much faster than the earlier reported approaches.
【Fund】: 国家自然科学基金项目( 60074040);; 国家杰出青年科学基金(60225006)。~~
【CateGory Index】: TM744
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