Abstract
With the rapid development of hydrogen production and storage technology, the development of hydrogen energy storage systems (HESSs) will bring fundamental changes to the structure of modern energy and power system. The combination of HESSs and battery energy storage systems (BESSs) for coordinated optimization can solve the imbalance between supply and demand of various energy sources and thus improve energy efficiency. In order to ensure the effectiveness of HESSs and BESSs planning, aiming at the minimum life cycle cost (LCC), system network loss and tie line switching power deviation, this paper uses multi-objective mayfly optimization (MOMA) to solve the Pareto non-dominated solution set of location and sizing planning schemes of energy storage systems (ESSs). Entropy weight method based grey target decision is used to select the best compromise solution from the Pareto non-dominated solution set. The simulation analysis is carried out based on the extended IEEE-33 node system.
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