Stochastic Control for Sustainable Hydrogen Generation in Standalone PV–Battery–PEM Electrolyzer Systems

Mohamed Aatabe (), Wissam Jenkal, Mohamed I. Mosaad and Shimaa A. Hussien
Additional contact information
Mohamed Aatabe: LISTI, National School of Applied Sciences, Ibn Zohr University, Agadir B.P. 1136, Morocco
Wissam Jenkal: LISTI, National School of Applied Sciences, Ibn Zohr University, Agadir B.P. 1136, Morocco
Mohamed I. Mosaad: Royal, Commission Yanbu Colleges Institutes, Yanbu Industrial College, Yanbu 46452, Saudi Arabia
Shimaa A. Hussien: Electrical Department, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia

Energies, 2025, vol. 18, issue 15, 1-30

Abstract: Standalone photovoltaic (PV) systems offer a viable path to decentralized energy access but face limitations during periods of low solar irradiance. While batteries provide short-term storage, their capacity constraints often restrict the use of surplus energy, highlighting the need for long-duration solutions. Green hydrogen, generated via proton exchange membrane (PEM) electrolyzers, offers a scalable alternative. This study proposes a stochastic energy management framework that leverages a Markov decision process (MDP) to coordinate PV generation, battery storage, and hydrogen production under variable irradiance and uncertain load demand. The strategy dynamically allocates power flows, ensuring system stability and efficient energy utilization. Real-time weather data from Goiás, Brazil, is used to simulate system behavior under realistic conditions. Compared to the conventional perturb and observe (P&O) technique, the proposed method significantly improves system performance, achieving a 99.9 % average efficiency (vs. 98.64%) and a drastically lower average tracking error of 0.3125 (vs. 9.8836). This enhanced tracking accuracy ensures faster convergence to the maximum power point, even during abrupt load changes, thereby increasing the effective use of solar energy. As a direct consequence, green hydrogen production is maximized while energy curtailment is minimized. The results confirm the robustness of the MDP-based control, demonstrating improved responsiveness, reduced downtime, and enhanced hydrogen yield, thus supporting sustainable energy conversion in off-grid environments.

Keywords: standalone PV microgrid; PEM hydrogen production; stochastic energy management; Markov decision process (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/15/3899/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/15/3899/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:15:p:3899-:d:1707039

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().