Research on Microgrid Capacity Optimization Configuration Based on PSO Algorithm

This paper presents research on microgrid capacity optimization configuration based on the Particle Swarm Optimization (PSO) algorithm, aiming to optimize energy management and economic benefits of microgrid systems. The study includes a complete MATLAB program that simulates microgrid operation dynamics and utilizes PSO algorithm to identify optimal capacity configuration solutions. The implementation features population initialization with random particle positions representing different capacity combinations, fitness evaluation through economic and technical constraints, and iterative velocity updates to converge toward global optima. Through this research, we gain deeper insights into microgrid performance characteristics and optimization methodologies, providing valuable guidance and references for future microgrid construction projects. The MATLAB code incorporates key functions for load forecasting, renewable energy generation modeling, and cost-benefit analysis, enabling comprehensive system evaluation under various operational scenarios.