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A multi-objective planning tool for the optimal supply of green hydrogen for an industrial port area decarbonization
This study addresses the challenge of decarbonizing highly energy-intensive Industrial Port Areas (IPA), focusing on emissions from various sources like ship traffic, warehouses, buildings, cargo handling equipment and hard-to-abate industry, typically hosted in port areas. The analysis and proposal...
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Published in: | Renewable energy 2024-10, Vol.232, p.120979, Article 120979 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | This study addresses the challenge of decarbonizing highly energy-intensive Industrial Port Areas (IPA), focusing on emissions from various sources like ship traffic, warehouses, buildings, cargo handling equipment and hard-to-abate industry, typically hosted in port areas. The analysis and proposal of technological solutions and their optimal integration in the context of IPA is a topic of growing scientific interest with considerable social and economic implications. Representing the main novelties of the work, this study introduces (i) the development of a novel IPA energy and green hydrogen hub located in a tropical region (Singapore); (ii) a multi-objective optimization approach to analyse, synthesize and optimize the design and operation of the hydrogen and energy hub, with the aim of supporting decision-making for decarbonization investments. A sensitivity analysis identifies key parameters affecting optimization results, indicating that for large hydrogen demands, imported ammonia economically outperforms other green hydrogen carriers. Conversely, local hydrogen production via electrolysis becomes economically viable when the capital cost of alkaline electrolyser drops by at least 30Â %. Carbon tax influences the choice of green hydrogen, but its price variation mainly impacts system operation rather than design. Fuel cells and batteries are not considered economically feasible solutions in any scenario. |
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ISSN: | 0960-1481 |
DOI: | 10.1016/j.renene.2024.120979 |