A Novel Particle Swarm Optimization Approach for Optimal Reactive Power Dispatch

TIn this paper, a solution to reactive power dispatch problem with a novel particle swarm ToptimizationT approach based on multi-agent systems (MAPSO) is presented. 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 quickly obtain optimal solution, each agent competes and cooperates with its neighbors, and it can also learn by using its knowledge. Making use of these agent-agent interactions and evolution mechanism of PSO, MAPSO realizes the purpose of optimizing the value of objective function. MAPSO applied for optimal reactive power dispatch is evaluated on an IEEE 30-bus power system and a practical 118-bus power system. Simulation results show that the proposed approach converges to better solutions much faster than the earlier reported approaches. The optimization strategy is general and can be used to solve other power system optimization problems as well.T