Research on Capacity Allocation of Wind-Solar Hybrid Energy Storage Microgrid Based on Improved Particle Swarm Optimization

Reasonable allocation of the capacities of micropower sources such as wind turbines, photovoltaics, and energy storage is a prerequisite for ensuring the economic and reliable operation of a microgrid. This paper investigates a method for capacity allocation in a hybrid energy storage system to address the volatility of wind power generation and enhance system stability. The k -means algorithm is used to cluster the collected wind power data, and empirical mode decomposition is applied to decompose typical power signals into different frequency bands, which are then assigned to a hybrid energy storage system consisting of supercapacitors and hydrogen storage. With the objective of minimizing the overall economic cost, a dynamically adjusted particle swarm optimization algorithm is proposed to optimize the capacity allocation of the hybrid energy storage system. Simulations verify the effectiveness of the proposed allocation method in reducing system costs and improving system stability.