Optimal Capacity Configuration of Hybrid Energy Storage Systems for Smoothing Photovoltaic Power Fluctuation

The quality of power output from photovoltaic (PV) systems is easily influenced by external environmental factors. To mitigate the power fluctuations that can impact the quality of electricity in the grid, this paper establishes an optimization model for capacity configuration of hybrid energy storage systems based on load smoothing. The net load data is processed using the Fast Fourier Transform (FFT) for frequency analysis. Considering various factors such as economic costs, capacity loss, cycle life, and state of charge of the energy storage devices, the objective is to minimize the total cost of the energy storage system. The Particle Swarm Optimization and Differential Evolution (PSO-DE) fusion algorithm is employed to determine the compensation frequency bands for each energy storage device and calculate the optimal capacity configuration for the hybrid energy storage system. Using a PV power station in Australia as an example, this paper compares different capacity configuration schemes for the hybrid energy storage system and proposes the optimal capacity configuration for the PV power station's hybrid energy storage system.