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Recent Trends in Optimizing Hydrogen Supply Networks
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Author(s): Devanshi Srivastava (Department of Chemical Engineering, Harcourt Butler Technical University, Kanpur, India), Adarsh Kumar Arya (Department of Chemical Engineering, Harcourt Butler Technical University, Kanpur, India), Toufik Mzili (Chouaib Doukkali University, Morocco)and Murali Pujari (Department of Chemical Engineering, University of Petroleum & Energy Studies, Bidholi, India)
Copyright: 2025
Pages: 24
Source title:
Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education
Source Author(s)/Editor(s): Toufik Mzili (Chouaib Doukkali University, Morocco)and Adarsh Kumar Arya (Harcourt Butler Technical University, India)
DOI: 10.4018/979-8-3373-1399-3.ch001
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Abstract
The extensive reliance on conventional fossil fuels escalates greenhouse gas emissions and exacerbates environmental pollution, necessitating an urgent energy shift. Consequently, the advancement and use of renewable energy are of paramount significance. Hydrogen is expected to progress in the following years as a replacement for fossil fuels among various renewable sources. However, the high cost of the hydrogen supply network (HSN) has provoked the researchers to use optimization techniques to optimize the (HSN). The present study analyzes modern optimization methods for (HSN) and thoroughly examines the 'Green hydrogen supply chain'(GHSC), including transportation, production, storage and consumption, emphasizing metaheuristic optimization (MO) applications. The difficulties inherent in each phase are highlighted, and the capacity of MO techniques to mitigate these difficulties is examined. The study also examines multi-objective methodologies for optimizing issues within this area.
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