Benders-and-Price approach for electric vehicle charging station location problem under probabilistic travel range. (December 2017)

• Record Type: Journal Article
• Authors: Lee, Chungmok; Han, Jinil
• Is Part Of: Transportation research. Volume 106(2017)
• Page Start: 130
• Page End: 152
• Publication Date: 2017-12
• Subjects: Electric vehicles -- Charging station location problem -- Flow refueling location model -- Probabilistic travel range -- Benders decomposition -- Column generation; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2017.10.011
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: We consider the electric vehicle charging station location problem. We introduce a probabilistic travel range when locating the charging stations. We develop a novel Benders-and-Price approach to solve the problem. Our algorithm is considerably faster than other approaches for real-life instances. Abstract: This paper investigates the optimal locations for refueling stations for electric vehicles. Electric vehicles have been successfully introduced into the market. However, their use seems to be limited to urban transport since recharging facilities are readily available only near home and work. Planning recharging infrastructure for electric vehicles is highly relevant because this will enable longer trips, including inter-state travel which requires multiple battery charges. Among various models to determine optimal locations of recharging stations, a flow refueling location model (FRLM) is considered in this study. It determines locations for recharging stations to maximize the flow that can travel between origin and destination pairs by refueling at built facilities. FRLM is extended by introducing a probabilistic consideration of the travel range which might vary depending on various factors including road conditions. We develop a mixed integer nonlinear programming formulation and propose a Benders-and-Price algorithm by combining the Benders decomposition and column generation to solve the proposed formulation. The proposed algorithm is validated using extensive computational experiments on two transport networks, including a real-life Texas highway network.