4.7 Article

Efficient and equitable transnational infrastructure planning for natural gas trucking in the European Union

期刊

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 257, 期 3, 页码 979-991

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2016.08.017

关键词

Location; Transportation; Alternative fuel; Station; Freight

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The European Union relies on oil for over 90% of its transportation fuels. To reduce this dependency, the EU is developing an integrated market for compressed (CNG) and liquefied (LNG) natural gas as alternatives to diesel for long-haul trucking. This paper develops a modeling approach for optimizing a subsidized European network of LNG truck stops based on the flow-refueling location model (FRLM). The FRLM locates stations to cover the maximum flow volume of origin-destination trips on their shortest paths. The FRLM explicitly accounts for the need for multiple refueling stops to serve long-distance trips given a user-specified vehicle driving range. In this paper, the FRLM maximizes covered flows in terms of ton-kilometers (tkm) rather than tons because tkm are proportional to the amount of diesel that can be replaced by LNG and the associated difference in carbon emissions. Nevertheless, despite the fact that maximizing covered tkm prioritizes longer shipments, the basic FRLM clusters all new stations in Germany, which has the densest concentration of flows. For subsidized stations promoting pan-European trucking, concentrating new stations in a few countries may not be politically desirable. We therefore introduce and compare several new side constraints for producing a more equitable distribution of covered flows across EU members, including transnational corridor constraints that require connectivity between different countries and partial country coverage constraints that require a minimum percentage coverage threshold in each country. The country coverage constraints show the most promise for offering decision makers distinct alternatives for a network of alternative-fuel stations across countries. (C) 2016 Elsevier B.V. All rights reserved.

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