Multi-objective Optimal Configuration of Electric-Hydrogen Hybrid Energy Storage System

Abstract

With the swift growth of hydrogen production and storage technology, the progress of hydrogen energy storage systems (HESSs) will bring radical revolution to the composition of 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, while it can improve energy efficiency. In order to ensure the effectiveness of BESSs and HESSs planning, aiming at the minimum life cycle cost (LCC), system network loss, tie line exchange power deviation, load fluctuation, and voltage fluctuation, this paper utilizes multi-objective particle swarm optimization (MOPSO) to solve the Pareto non-dominated solution set of ESSSs location and capacity planning scheme. Besides, the grey target decision based on the entropy weight method (EWM) is used to select the best compromise solution in the Pareto non-dominated solution set. In addition, the typical operation scenario set of source load is obtained by fuzzy kernel C-means (FKCM) clustering algorithm, while the simulation analysis is carried out on the basis of the extended IEEE-33 bus system. The simulation results show that MOPSO realizes the minimum LCC of the electric-hydrogen hybrid energy storage system, upon which its voltage quality, power stability, network loss, and load fluctuation are better than those non-optimized.