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Hydrogen Refueling Stations and Carbon Emission Reduction of Coastal Expressways: A Deployment Model and Multi-Scenario Analysis

Abstract

Hydrogen is considered to the ultimate solution to achieve carbon emission reduction due to its wide sources and high calorific value, as well as non-polluting, renewable, and storable advantages. This paper starts from the coastal areas, uses offshore wind power hydrogen production as the hydrogen source, and focuses on the combination of hydrogen supply chain network design and hydrogen expressway hydrogen refueling station layout optimization. It proposes a comprehensive mathematical model of hydrogen supply chain network based on cost analysis, which determined the optimal size and location of hydrogen refueling stations on hydrogen expressways in coastal areas. Under the multi-scenario and multi-case optimization results, the location of the hydrogen refueling station can effectively cover the road sections of each case, and the unit hydrogen cost of the hydrogen supply chain network is between 11.8 and 15.0 USD/kgH2 . Meanwhile, it was found that the transportation distance and the number of hydrogen sources play a decisive role on the cost of hydrogen in the supply chain network, and the location of hydrogen sources have a decisive influence on the location of hydrogen refueling stations. In addition, carbon emission reduction results of hydrogen supply chain network show that the carbon emission reduction per unit hydrogen production is 15.51 kgCO2/kgH2 at the production side. The CO2 emission can be reduced by 68.3 kgCO2/km and 6.35 kgCO2/kgH2 per unit mileage and per unit hydrogen demand at the application side, respectively. The layout planning utilization of hydrogen energy expressway has a positive impact on energy saving and emission reduction.

Funding source: This work was funded by the National Natural Science Foundation of China (51906026), Dalian High Level Talent Innovation Support Program (2021RQ132), the Fundamental Research Funds for the Central Universities (3132022224), China Postdoctoral Science Foundation (2020M680928), Natural Science Foundation of Liaoning Province (2020-BS-067), the National Key Research and Development Program of China (2019YFE0116400).
Related subjects: Applications & Pathways
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/content/journal3719
2022-07-20
2022-10-02
http://instance.metastore.ingenta.com/content/journal3719
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