Mapping hydrogen demand for heavy-duty vehicles: a spatial disaggregation approach

Q2 Energy
Warsini Handayani, Xuan Zhu, Fang Lee Cooke
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引用次数: 0

Abstract

Hydrogen is the key to decarbonising heavy-duty transport. Understanding the distribution of hydrogen demand is crucial for effective planning and development of infrastructure. However, current data on future hydrogen demand is often coarse and aggregated, limiting its utility for detailed analysis and decision-making. This study developed a spatial disaggregation approach to estimating hydrogen demand for heavy-duty trucks and mapping the spatial distribution of hydrogen demand across multiple scales in Australia. By integrating spatial datasets with economic factors, market penetration rates, and technical specifications of hydrogen fuel cell vehicles, the approach disaggregates the projected demand into specific demand centres, allowing for the mapping of regional hydrogen demand patterns and the identification of key centres of hydrogen demand based on heavy-duty truck traffic flow projections under different scenarios. This approach was applied to Australia, and the findings offered valuable insights that can help policymakers and stakeholders plan and develop hydrogen infrastructure, such as optimising hydrogen refuelling station locations, and support the transition to a low-carbon, heavy-duty transport sector.

绘制重型车辆的氢需求:一种空间分解方法
氢是重型运输脱碳的关键。了解氢需求的分布对基础设施的有效规划和发展至关重要。然而,目前关于未来氢需求的数据通常是粗糙和汇总的,限制了其对详细分析和决策的效用。本研究开发了一种空间分解方法来估计重型卡车的氢需求,并绘制了澳大利亚多个尺度上氢需求的空间分布。该方法将空间数据集与氢燃料电池汽车的经济因素、市场渗透率和技术规范相结合,将预测需求分解为特定的需求中心,从而可以绘制区域氢需求模式,并根据不同情景下的重型卡车交通流量预测确定氢需求的关键中心。该方法应用于澳大利亚,研究结果提供了有价值的见解,可以帮助政策制定者和利益相关者规划和发展氢基础设施,例如优化加氢站的位置,并支持向低碳、重型运输部门的过渡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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