An enhanced predictive energy management of a green hydrogen integrated microgrid based on correlation analysis considering uncertain conditions

An enhanced predictive energy management of a green hydrogen integrated microgrid based on correlation analysis considering uncertain conditions

The increasing adoption of renewable energy sources presents unique challenges due to their unpredictable nature and the need for efficient energy storage management. Maintaining grid stability requires robust energy storage solutions to manage the variability as the power industry shifts towards renewable generation. This paper focuses on developing a reliable model based on experimental predictive correlation for a green hybrid grid-integrated microgrid that utilizes hydrogen storage to mitigate energy fluctuation. The goal is to maintain frequency and voltage stability across various operating scenarios using hydrogen as the primary energy storage system. A comprehensive framework is presented for modelling a hybrid energy system that combines solar, hydrogen storage, fuel cells, and lithium battery storage. The initial step in this study involves experimental investigation to formulate a predictive correlation index (PCI) for hydrogen-based energy systems, concentrating on the relationship between hydrogen flowrate, pressure, temperature, and the resulting electrical outputs, voltage, and current. This formulation is then used to develop an enhanced energy management coordination strategy based on the correlation index, leveraging the capabilities of model predictive control to anticipate fluctuations in energy demand and supply. A cloud-based Internet of Things (IoT) platform is utilized to monitor system performance in real-time under various conditions, manage storage efficiently, and enhance security by minimizing vulnerabilities. Numerical findings confirm that the hybrid predictive scheme reduces frequency deviation within ±0.16 % and constrains voltage variation to approximately ±4 %. Here, the experimental PCI values identify an optimal hydrogen operating range of 0.3–0.4 bar for reliable performance. Performance benchmarking further demonstrates that, compared with conventional droop-based methods reported in earlier studies, the proposed correlated hybrid control strategy achieves improved transient response and lower steady-state error, ensuring more reliable coordination of hydrogen and battery storage. The results prove that the proposed predictive coordination strategy effectively mitigates voltage and frequency fluctuations during transient situations by optimally controlling the hydrogen storage within the microgrid. This outcome underscores the positive impact of the proposed predictive coordination strategies in enhancing continuous power supply and improving the overall efficiency of grid-integrated systems.

© 2026. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/