Optimal operation of photovoltaic-battery systems with modular electrolyzer degradation awareness and economic considerations

Protecting the environment from emissions requires widespread adoption of renewable energy resources alongside both short-term and long-term storage solutions like hydrogen-based systems. However, its crucial to carefully evaluate the economic and operational aspects of the hydrogen system, to ensure proper degradation monitoring and cost management. Most studies in literature tend to focus on either cost or degradation independently. Therefore, this work introduces an optimal framework to simultaneously minimize cost of hydrogen (CoH) and voltage degradation rates within a scalable, modular electrolyzer system by achieving optimal energy management and power allocations among electrolyzer stacks in the islanded microgrid. The framework incorporates variations in Faradaic efficiency to reflect the impact of renewable energy intermittency and employs a look-ahead strategy for proactive decision-making under uncertainty. The resulting non-linear, multimodal optimization problem is solved using the Artificial Hummingbird Algorithm (AHA), a metaheuristic technique known for its strong global search capability and resistance to local optima. The proposed approach is evaluated versus several state-of-the-art approaches using key performance metrics including CoH, voltage degradation rates and various system efficiencies, are calculated to provide detailed insights into the performance of the proposed method compared to existing approaches. The results mainly show that the proposed approach optimally allocates power across system components and among the modular electrolyzer stacks in the islanded microgrid, achieving CoH within 0.15%–0.75% of the approach that focuses primarily on the economic aspect. Furthermore, it significantly reduces voltage degradation rates by 43% and improves various system efficiencies by 2.65%.