Optimization and control strategy for reactive–power and voltage–quality improvement in distribution networks based on GA–MOPSO

Abstract

: Because power–quality mitigation devices in distribution networks often lack a system–wide optimal regulation strategy, this paper proposes an integrated optimization and control strategy based on a genetically enhanced multi–objective particle swarm optimization (GA–MOPSO) algorithm to coordinate the control schemes of reactive–power devices. Crossover–based genetic operations are incorporated into the multi–objective computation, enabling MOPSO to explore a broader search space and further accelerate convergence. A 10 kV simulation model is built on the IEEE 33–bus system, with dispersed integration of loads exhibiting reactive–power deficiency to emulate power–quality issues. Simulation results verify the feasibility and high efficiency of the proposed optimization and control strategy.