4.7 Article

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

期刊

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
卷 47, 期 52, 页码 21897-21907

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2022.05.036

关键词

Hydrogen economy; Python tool; GUI; Optimization; MILP

资金

  1. ExxonMobil through the Singapore Energy Centre [LAW-2019-3484 (EM11161.TO5)]

向作者/读者索取更多资源

This paper introduces a tool called HEART for assessing and planning the hydrogen economy in the ASEAN region. The tool enables techno-enviro-economic analysis, demand projection, and supply chain optimization of hydrogen. The case study demonstrates the tool's capability to provide useful results and optimize the hydrogen industry.
In the past decades, H-2 has attracted significant attention as a potentially low, zero, or negative-emissions fuel depending on how it is produced. However, how H-2 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 H-2 production and H-2 transport, project H-2 demand, and carry out the optimization and planning of H-2 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 H-2. Most importantly, by using HEART, H-2 supply chain pathways to meet projected demand can be obtained and optimized for total cost or total emissions. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

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