Multiagent based particle swarm optimization approach to economic dispatch with security constraints

This paper proposes a new evolutionary approach named as multi agent particle swarm optimization (MAPSO) algorithm for solving economic dispatch with security constraints (line flow and bus voltage). This method integrates multiagent systems (MAS) and particle swarm optimization (PSO) to form a new algorithm, multiagent particle swarm optimization algorithm. In MAPSO, an agent 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 obtain optimal solution, each agent competes and cooperates with its neighbor and it can also learn by using its knowledge. Making use of these agent-agent interactions, MAPSO realizes the purpose of minimizing the objective function value. MAPSO is applied to two representative systems i.e. IEEE 14 bus and IEEE 30 bus systems. Simulation results show that proposed approach gives better solution than earlier reported approaches.