Quasi Oppositional Population Based Global Particle Swarm Optimizer With Inertial Weights (QPGPSO-W) for Solving Economic Load Dispatch Problem

In recent years, power companies have shown increasing interest in making strategic decisions to maintain profitable energy systems. Economic Load Dispatch (ELD) is a complex decision-making process where the output of entire generating units must be set way that results overall economic operation system. Moreover, it constrained multi-objective optimization problem. Now days, there tendency use metaheuristic methods deal with complexity ELD Particle swarm (PSO) subclass inspired by fish schooling and bird flocking behaviors. However, performance PSO highly dependent on fitness landscapes can lead local optima stagnation premature convergence. Therefore, proposed study, two new variants called global particle optimizer inertia weights (GPSO-w) quasi-oppositional population based (QPGPSO-w) are address The problem formulated as an validation performed IEEE standards (3, 6, 13, 15, 40 & 140) unit Korean grid test systems under numerous constraints obtained compared several techniques presented literature. convex showed excellent cost-effectiveness, while for non-convex sequential quadratic programming (SQP) was added discover minima even more efficiently. were successful solving yielded better reported selected cases. It further inferred less algorithmic parameters reflected improved exploration convergence characteristics.