Capacity Optimization of Hybrid Energy Storage System Based on Improved Zebra Optimization Algorithm

A hybrid energy storage system capacity optimization is proposed to address the challenges of stochasticity and intermittency inherent in renewable energy generation and to improve the stability and economy of wind and solar power microgrids. The optimization takes the lowest cost of the whole life cycle of the hybrid energy storage system as the optimization objective, and takes the load shortage rate and other system operation indexes as the constraints to establish the optimization model. On this basis, the zebra optimization algorithm(ZOA) is improved so that the convergence speed and accuracy of the algorithm are increased. Finally, the optimization results of the improved zebra optimization algorithm(IZOA) are compared with the basic ZOA and the particle swarm optimization(PSO) by means of an arithmetic example, which verifies the superiority of IZOA for hybrid energy storage capacity allocation.