Coordinated Optimization of Distributed Energy Resources and Energy Storage Allocation in Park

In the context of constructing a new type power system, the continuous rise in carbon emission costs and the uncertainty of source-load output have a crucial impact on the capacity configuration of park-level microgrids. To address the problem of optimal allocation of distributed energy resources and energy storage within microgrids, this paper aims to minimize life-cycle investment and operation costs while achieving zero-carbon consumption. Models of wind, photovoltaic, storage, and load units are established, and a user-interactive visualization interface is developed on the MATLAB platform. Particle swarm optimization, genetic algorithm, and simulated annealing are applied for multi-objective coordinated optimization of the microgrid system, ultimately determining the optimal wind-PV-storage configuration scheme.