Multi-Objective Optimal Scheduling of Microgrids Based on Improved Particle Swarm Optimization Algorithm

As an important part of smart grid optimization, microgrid optimal scheduling is of great significance to reduce energy consumption and environmental pollution. A multi-obj ective optimal scheduling model of microgrid in grid-connected mode is proposed, which is coordinated with economy and environmental protection. Under the condition of satisfying the system constraints, the optimization problem of microgrid system composed of photovoltaic, wind turbines, micro gas turbines, diesel engines and batteries is studied. Then the improved particle swarm optimization algorithm is used to solve the multi-obj ective optimization model. The improved particle swarm optimization algorithm considers the improvement of inertia factor and particle adaptive mutation. The simulation results show that the model can effectively reduce the costs of electricity and environmental protection, and verify the superior performance of the improved particle swarm optimization algorithm.