Hydrogen Economy Assessment & Resource Tool (HEART): A python-based tool for ASEAN H2 roadmap study

In the past decades, H2 has attracted significant attention as a potentially low, zero, or negative-emissions fuel depending on how it is produced. However, how H2 will evolve in terms of its production, demand, and transport is not very clear. To help fill this gap, we developed a Python-based tool...

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Published in:International journal of hydrogen energy Vol. 47; no. 52; pp. 21897 - 21907
Main Authors: Hong, Xiaodong, Garud, Sushant S., Thaore, Vaishali B., Karimi, Iftekhar A., Farooq, Shamsuzzaman, Wang, Xiaonan, Usadi, Adam K., Chapman, Bryan R., Johnson, Robert A.
Format: Journal Article
Language:English
Published: Elsevier Ltd 22.06.2022
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ISSN:0360-3199, 1879-3487
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Abstract In the past decades, H2 has attracted significant attention as a potentially low, zero, or negative-emissions fuel depending on how it is produced. However, how H2 will evolve in terms of its production, demand, and transport is not very clear. To help fill this gap, we developed a Python-based tool called the Hydrogen Economy Assessment & Resource Tool (HEART), specifically focused on the Association of Southeast Asian Nations (ASEAN) region. The tool consists of three parts: a user-friendly GUI, a default database consisting of costs and emissions for various supply/demand pathways, and an analysis and optimization engine. Users can use the default data and/or user inputs to run case studies for insightful results. The analysis and optimization engine can carry out techno-enviro-economic analysis for H2 production and H2 transport, project H2 demand, and carry out the optimization and planning of H2 supply chain over a long-term period. In this paper, we introduce the framework of HEART, the workflow of various projects, and show the capabilities and strengths of HEART through a case study. The case study indicates the tool can provides many useful results, like the landed cost and carbon footprint of H2. Most importantly, by using HEART, H2 supply chain pathways to meet projected demand can be obtained and optimized for total cost or total emissions. [Display omitted] •A Python-based tool is developed for hydrogen economy planning and optimization.•The framework, workflow, and capabilities of HEART is introduced.•Hydrogen supply chains for multiple sectors are planned for an ASEAN case study.
AbstractList In the past decades, H2 has attracted significant attention as a potentially low, zero, or negative-emissions fuel depending on how it is produced. However, how H2 will evolve in terms of its production, demand, and transport is not very clear. To help fill this gap, we developed a Python-based tool called the Hydrogen Economy Assessment & Resource Tool (HEART), specifically focused on the Association of Southeast Asian Nations (ASEAN) region. The tool consists of three parts: a user-friendly GUI, a default database consisting of costs and emissions for various supply/demand pathways, and an analysis and optimization engine. Users can use the default data and/or user inputs to run case studies for insightful results. The analysis and optimization engine can carry out techno-enviro-economic analysis for H2 production and H2 transport, project H2 demand, and carry out the optimization and planning of H2 supply chain over a long-term period. In this paper, we introduce the framework of HEART, the workflow of various projects, and show the capabilities and strengths of HEART through a case study. The case study indicates the tool can provides many useful results, like the landed cost and carbon footprint of H2. Most importantly, by using HEART, H2 supply chain pathways to meet projected demand can be obtained and optimized for total cost or total emissions. [Display omitted] •A Python-based tool is developed for hydrogen economy planning and optimization.•The framework, workflow, and capabilities of HEART is introduced.•Hydrogen supply chains for multiple sectors are planned for an ASEAN case study.
Author Thaore, Vaishali B.
Johnson, Robert A.
Garud, Sushant S.
Chapman, Bryan R.
Farooq, Shamsuzzaman
Wang, Xiaonan
Usadi, Adam K.
Hong, Xiaodong
Karimi, Iftekhar A.
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