Locating Alternative Fuel Stations for Maximizing Coverage and Ensuring Sufficient Spacing: a Case Study of CNG Truck Fueling

Qing Zhong, Daoqin Tong, Michael Kuby, Fangwu Wei, John Fowler, Keiron Bailey

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

While a number of optimization models have been proposed for siting refueling/recharging stations for alternative fuel/electric vehicles, many of these approaches require detailed origin–destination (OD) data of refueling trips that are often very costly or challenging to obtain. This paper introduces two new arc-based coverage models for locating alternative fuel stations for regions where OD data are unavailable or unsuitable. Station spacing parameters are proposed to reduce redundant coverage while helping fill in regional coverage gaps. The first model is more suitable for early stages of planning, while the second addresses coverage overlap issues during later stages when a denser station network is formed. Both models can handle cases with a set of pre-existing stations. The new models are applied to planning a network of compressed natural gas (CNG) fueling stations for heavy-duty CNG-powered trucking in the Southwest USA. The models are generalizable to other regions, fuels, and vehicle types when applicable OD data are lacking.

Original languageEnglish (US)
Pages (from-to)455-470
Number of pages16
JournalProcess Integration and Optimization for Sustainability
Volume3
Issue number4
DOIs
StatePublished - Dec 1 2019

Keywords

  • Alternative fuel station location
  • Annual average daily traffic (AADT) coverage
  • CNG truck fueling
  • Location models

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law
  • Pollution
  • Waste Management and Disposal
  • Geography, Planning and Development
  • Control and Systems Engineering
  • Chemical Engineering(all)

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