Multi-agent particle swarm optimization algorithm for reactive power optimization

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.