Techno-Economic Assessment of Battery Energy Storage Technologies and Energy Management Strategies for Hydrogen Hosting Capacity in Microgrids

This paper presents a techno-economic evaluation of battery energy storage systems (BESSs) integrated into hydrogen-based microgrids (MGs). Eight BESS technologies are investigated to quantify their impact on the hydrogen energy storage hosting capacity (HC) and MG performance. A detailed techno-economic model is developed to capture the key technical and economic characteristics of BESSs. The model considers depth of discharge (DOD), round-trip efficiency, capital cost, replacement cost, operation and maintenance cost and salvage value. Two energy management strategies (EMSs), namely hydrogen-prioritized and battery-prioritized schemes, are formulated to assess their influence on hydrogen utilization, BESS sizing and system operation. An optimization framework is established to minimize the levelized cost of energy (LCOE) and the Stellar Oscillation Optimizer is employed to solve the problem. The results indicate that high-efficiency, high-DOD battery technologies significantly reduce the required number of battery units and the LCOE under variable-sizing scenarios, whereas lower-capital-cost technologies exhibit superior performance under fixed-sizing conditions. The hydrogen-prioritized EMS decreases battery capacity requirements but increases hydrogen utilization. While the battery-prioritized EMS reduces hydrogen reliance at the expense of higher battery cycling and operating frequency. Under the battery-prioritized EMS, low-cost BESS technologies require 0.8-3.3% more battery units. Whereas higher-cost technologies achieve up to a 1.6% reduction in battery count. An increase of about 50% in the HC of PEM fuel cell is achieved. Furthermore, the choice of BESS technology significantly affects environmental performance. Variations in CO2 emissions of up to 3.11 tonnes is reported for the same MG configuration. A sensitivity analysis is also conducted to evaluate MG performance under variations in load demand, RES generation, battery capital cost, minimum DOD, and operating efficiency.