基于粒子群算法的微电网系统在模式切换下的多目标优化调度OA

With the rapid development of distributed and clean energy,microgrids have become a key component of new power systems.To ensure their stable operation during grid-connected and island mode switching,it is important to study scheduling optimization strategies that are both reliable and robust.This paper addresses issues such as fluctuating renewable energy output,changes in supply-demand structure,and the complexity of optimization objectives during microgrid operation mode switching by establishing a dynamic scheduling model with dual objectives of operational cost and environmental protection cost.The model comprehensively considers the operational characteristics of distributed units such as wind power,photovoltaics,and energy storage,and incorporates constraints including power balance,output limits,and energy storage management to ensure the safety and continuity of the switching process.A multi-objective particle swarm optimization algorithm is employed to solve the model.Simulation results demonstrate that this method effectively captures the impact of operation mode switching on scheduling behavior.The obtained Pareto solution set exhibits a well-distributed and diverse distribution,and the optimized scheme achieves significant improvements in both operational cost and environmental cost.Particularly in island mode,the coordinated operation of storage batteries,diesel generators,and micro gas turbines effectively ensures the stability of the system's power supply,verifying the adaptability and robustness of the proposed model and algorithm in engineering applications.