A multi-objective optimal power flow using particle swarm optimization

This paper presents a multi-objective optimal power flow technique using particle swarm optimization. Two conflicting objectives, generation cost, and environmental pollution are minimized simultaneously. A multi-objective particle swarm optimization method is used to solve this highly nonlinear and non-convex optimization problem. A diversity preserving technique is incorporated to generate evenly distributed Pareto optimal solutions. A fuzzy membership function is proposed to choose a compromise solution from the set of Pareto optimal solutions. The algorithm is tested on IEEE 30 and 118 bus systems and its effectiveness is illustrated.