A novel demand response framework for the optimal design of hydrogen-ammonia hybrid microgrids

In standalone applications, hybrid microgrids are showing promise as a means of satisfying consumers’ combined needs for gas, heat, and power. While green hydrogen and green ammonia have been studied separately as energy carriers in earlier research, blended hydrogen-ammonia fuels that can directly feed gas loads or indirectly assist in the generation of electricity have received less attention. In order to achieve technical, economic, reliability, and environmental goals, this study proposes a novel demand response strategy for the optimal sizing and operation of a multiuse hybrid microgrid. The proposed strategy increases the viability of employing renewable resources to cover all energy demands by extending participation beyond electrical loads to include gas and heat loads. To address hourly variations in generation and demand, the 24-hour operation is divided into dynamic intervals in which selected power, gas, and heat loads are shifted from periods of low renewable generation to periods of surplus production, supported by customer incentives. In terms of the environment, the system collects oxygen that is generated as a byproduct of several energy conversion processes, making it suitable for use in industrial and medical settings. To fully substitute natural gas in meeting gas demand, a blended ammonia-hydrogen fuel is also introduced as a decarbonization approach. To reduce overall cost, unmet load, curtailed energy, and emissions, the optimization framework uses a multi-objective function that is weighted using the Analytical Hierarchy Process (AHP). Two optimization techniques, teaching-learning-based optimization and particle swarm optimization, are used to assess the efficacy of the proposed methodology under various circumstances.

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Publication Details

Journal
Applied Energy
Published
2026-05-29
DOI
https://doi.org/10.1016/j.apenergy.2026.128074
Primary Topic
Ammonia Synthesis and Nitrogen Reduction
Type
article
Field-Weighted Citation Impact
0.00

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article

A novel demand response framework for the optimal design of hydrogen-ammonia hybrid microgrids

Adam Y. Sulaiman, Fujin Deng, Sayed Abulanwar, Abdelrahman Mewafy et al.
Applied Energy
Ammonia Synthesis and Nitrogen Reduction
article

A novel demand response framework for the optimal design of hydrogen-ammonia hybrid microgrids

Adam Y. Sulaiman, Fujin Deng, Sayed Abulanwar, Abdelrahman Mewafy, Islam Ismael, Sahar Kaddah
article en

Abstract

In standalone applications, hybrid microgrids are showing promise as a means of satisfying consumers’ combined needs for gas, heat, and power. While green hydrogen and green ammonia have been studied separately as energy carriers in earlier research, blended hydrogen-ammonia fuels that can directly feed gas loads or indirectly assist in the generation of electricity have received less attention. In order to achieve technical, economic, reliability, and environmental goals, this study proposes a novel demand response strategy for the optimal sizing and operation of a multiuse hybrid microgrid. The proposed strategy increases the viability of employing renewable resources to cover all energy demands by extending participation beyond electrical loads to include gas and heat loads. To address hourly variations in generation and demand, the 24-hour operation is divided into dynamic intervals in which selected power, gas, and heat loads are shifted from periods of low renewable generation to periods of surplus production, supported by customer incentives. In terms of the environment, the system collects oxygen that is generated as a byproduct of several energy conversion processes, making it suitable for use in industrial and medical settings. To fully substitute natural gas in meeting gas demand, a blended ammonia-hydrogen fuel is also introduced as a decarbonization approach. To reduce overall cost, unmet load, curtailed energy, and emissions, the optimization framework uses a multi-objective function that is weighted using the Analytical Hierarchy Process (AHP). Two optimization techniques, teaching-learning-based optimization and particle swarm optimization, are used to assess the efficacy of the proposed methodology under various circumstances.

Applied EnergyVol. 419
Queen's University Belfast (GB), Mansoura University (EG), Applied Science University (BH), Southeast University (CN), University College of Bahrain (BH)
National Key Research and Development Program of China Stem Cell and Translational Research
Affordable and clean energy
Openalex Percentile: Top 16%
Ammonia Synthesis and Nitrogen Reduction
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