The need for deep decarbonization of the transport sector cannot be understated, as it accounts for about the 25% of greenhouse gas emissions in Europe. Developing hydrogen-based trucks is one of the viable solutions for exploiting green hydrogen and reaching climate neutrality. This work presents an optimization framework to optimally place Hydrogen Refueling Stations (HRS) for hydrogen-based trucks under technical, policy and regulatory constraints. It relies on an EU heavy-duty road freight transport database adapted to the latest publicly available statistics to update the demand intensity. A revised Node Capacitated Flow Refueling Location Model is proposed to minimize the number of HRS to be sited on the highway network. The node capacity constraint considers standard sized HRS with a maximum daily capacity ranging from 500 (S-sized) to 4000 kg (XL-sized). The framework can be a useful evaluation tool to strategically site HRS, both for policymakers and stakeholders. To this end, the Italian highway network was evaluated as a case study, finding that at least 78 HRS nodes are required across the road network if a 10% share of hydrogen vehicles is considered, as planned in the Italian National Recovery and Resilience Plan. The median utilization factor of the refueling stations is 67.5%, ranging from 49% for the S-sized to 86% for the XL-sized, which are located mainly in northern Italian regions. To effectively reduce emissions in road freight transport, results show that at least 368 MW of additional equivalent photovoltaic capacity is needed to produce entirely green hydrogen, reducing the greenhouse gases emissions associated to the road freight transport by 6.5%.
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Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China
Wang, Shiqi
Peng, Zhenhan
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Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China
Peng, Zhenhan
Wang, Pinxi
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Tsinghua Univ, Sch Vehicle & Mobil, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China
Beijing Transport Inst, 9 Liuliqiao South Lane, Beijing 100073, Peoples R China
Beijing Key Lab Transport Energy Conservat & Emiss, 9 Liuliqiao South Lane, Beijing 100073, Peoples R ChinaHong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China
Wang, Pinxi
Chen, Anthony
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Kowloon, Hong Kong, Peoples R China
Hong Kong Polytech Univ, Smart Cities Res Inst, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China
Chen, Anthony
Zhuge, Chengxiang
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Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China
Hong Kong Polytech Univ, Res Inst Sustainable Urban Dev, Kowloon, Hong Kong, Peoples R China
Hong Kong Polytech Univ, Smart Cities Res Inst, Hong Kong, Peoples R China
Hong Kong Polytech Univ Shenzhen Res Inst, Shenzhen, Peoples R ChinaHong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China