Renewable-Centric Energy Management in Hydrogen Microgrids: A Multi-Objective Framework for Optimized Scheduling and Sustainability

Authors

  • B. N. Kerama Department of Electrical and Electronics Engineering, Jomo Kenyatta University of Agriculture & Technology, P. O Box 62000-00100, Nairobi, Kenya

DOI:

https://doi.org/10.54536/jsere.v1i2.5187

Keywords:

Energy Management System, Hydrogen-Based Microgrid, Off-Grid Power Systems, Operational Optimization, Renewable Energy Integration, Sustainable Energy Solutions

Abstract

As the transition to renewable energy accelerates globally, integrating variable energy sources such as solar and wind into standalone systems poses new operational and economic challenges. Hydrogen-based microgrids (H-MGs) offer a promising solution by serving as both energy storage and conversion systems capable of stabilizing renewable power. This study proposes a novel multi-objective optimization framework tailored for standalone H-MGs with a strong emphasis on maximizing renewable energy utilization. The framework combines predictive modeling, real-time control, and mixed-integer linear programming (MILP) to coordinate the operation of renewable sources, electrolyzers, hydrogen storage, and fuel cells. It incorporates advanced renewable forecasting and adaptive scheduling strategies to optimize energy dispatch while reducing costs and enhancing system reliability. A case study on an off-grid industrial facility demonstrates the framework’s effectiveness, achieving a 38% increase in renewable energy penetration, a 23% reduction in energy costs, and a 35% improvement in reliability compared to conventional approaches. The results underscore the critical role of hydrogen in enabling high-renewable microgrids and lay the foundation for future integration with AI, smart grids, and decentralized energy markets.

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Published

2025-12-30

How to Cite

Kerama, B. N. (2025). Renewable-Centric Energy Management in Hydrogen Microgrids: A Multi-Objective Framework for Optimized Scheduling and Sustainability. Journal of Sustainable Engineering & Renewable Energy, 1(2), 36-44. https://doi.org/10.54536/jsere.v1i2.5187

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