A threshold covering flow-based location model to build a critical mass of alternative-fuel stations

To facilitate the transition to alternative-fuel vehicles (AFVs), researchers have developed models for optimally locating an initial refueling infrastructure for AFVs with limited driving range. Recently, clustering of stations has emerged as a strategy to encourage consumers to purchase AFVs by building a critical mass of stations. Clustering approaches, however, have focused on serving demands represented as nodes or arcs rather than origin-destination (O-D) trips. This study proposes a Threshold Coverage extension to the original Flow Refueling Location Model that focuses on the percentage of a zone's O-D trips that can be successfully completed given a typical driving range and location of stations. It is motivated by the idea that drivers in an area will not purchase an AFV unless a critical mass of the trips they regularly make can be completed. Therefore, the new model optimally locates p refueling stations on a network to maximize the sum of weighted demand of covered origin zones, where “covered” means that the zone exceeds a specified threshold percentage of their total outbound round trips that are refuelable. The model is tested on networks for Orlando and the state of Florida. As the threshold percentage is raised, fewer zones can surpass the threshold. Covered nodes increasingly cluster together, as do stations for serving their O-D flows. The model's policy implementation will provide managerial insights for some key concerns of the industry, such as geographic equity vs. critical mass, from a new perspective.