Optimal Dispatching Control Method for Photovoltaic Storage and Charging Microgrid Based on Multiobjective

As the global energy structure transforms toward low-carbonization and renewable energy, microgrids have attracted widespread attention as a new type of energy management system. This paper proposes a Multi-Objective Optimal Dispatch Control Method for PV-Integrated Microgrids with Energy Storage and Charging Loads (MOODCM-PVESCL) based on multi-objective optimization, aiming to minimize economic costs, minimize carbon emissions and optimize supply and demand balance. The microgrid model mainly includes photovoltaic power generation system, energy storage system, load and power grid. In order to deal with the conflicts among multiple objectives, this paper adopts the Pareto optimization method and solves it through an improved genetic algorithm, and proposes an adaptive multi-population genetic algorithm (AMGA). The algorithm enhances global search capability and population diversity through adaptive mutation rate and multipopulation strategy, effectively improving optimization efficiency and accuracy. Through simulation verification, the MOODCMPVESCL method performs well in improving the economy, environmental friendliness and operation stability of microgrids, and provides new solutions and theoretical support for the optimal scheduling of independent microgrids.