Development of Electric Vehicle Charging Corridor for South Carolina

We apply a flow-based location model, called Multipath Refueling Location Model (MPRLM), to develop an electric vehicle (EV) public charging infrastructure network for enabling long-haul inter-city EV trips. The model considers multiple deviation paths between every origin-destination (O-D) pairs an...

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Main Author: Shengyin Li, Ph.D. candidate
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2015-01-01
Series:International Journal of Transportation Science and Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2046043016301708
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author Shengyin Li, Ph.D. candidate
author_facet Shengyin Li, Ph.D. candidate
author_sort Shengyin Li, Ph.D. candidate
collection DOAJ
description We apply a flow-based location model, called Multipath Refueling Location Model (MPRLM), to develop an electric vehicle (EV) public charging infrastructure network for enabling long-haul inter-city EV trips. The model considers multiple deviation paths between every origin-destination (O-D) pairs and relaxes the commonly adopted assumption that travelers only take a shortest path between O-D pairs. This model is a mixed-integer linear program, which is intrinsically difficult to solve. With greedy-adding based heuristics, the MPRLM is applied to optimally deploy EV fast charging stations along major highway corridors in South Carolina. Compared to engineering methods, the optimization model reduces the capital cost of establishing a fast charging network by two thirds. We also explore the interplay between the spatial distributions of cities, vehicle range, and routing deviation tolerance as well as their impacts on the locational strategies.
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spelling doaj.art-3869bcb2025c4251a109e49fc31b997b2023-08-02T02:16:31ZengKeAi Communications Co., Ltd.International Journal of Transportation Science and Technology2046-04302015-01-014439541110.1016/S2046-0430(16)30170-8Development of Electric Vehicle Charging Corridor for South CarolinaShengyin Li, Ph.D. candidateWe apply a flow-based location model, called Multipath Refueling Location Model (MPRLM), to develop an electric vehicle (EV) public charging infrastructure network for enabling long-haul inter-city EV trips. The model considers multiple deviation paths between every origin-destination (O-D) pairs and relaxes the commonly adopted assumption that travelers only take a shortest path between O-D pairs. This model is a mixed-integer linear program, which is intrinsically difficult to solve. With greedy-adding based heuristics, the MPRLM is applied to optimally deploy EV fast charging stations along major highway corridors in South Carolina. Compared to engineering methods, the optimization model reduces the capital cost of establishing a fast charging network by two thirds. We also explore the interplay between the spatial distributions of cities, vehicle range, and routing deviation tolerance as well as their impacts on the locational strategies.http://www.sciencedirect.com/science/article/pii/S2046043016301708Electric vehicleCharging stationCombinatorial optimizationHeuristics
spellingShingle Shengyin Li, Ph.D. candidate
Development of Electric Vehicle Charging Corridor for South Carolina
International Journal of Transportation Science and Technology
Electric vehicle
Charging station
Combinatorial optimization
Heuristics
title Development of Electric Vehicle Charging Corridor for South Carolina
title_full Development of Electric Vehicle Charging Corridor for South Carolina
title_fullStr Development of Electric Vehicle Charging Corridor for South Carolina
title_full_unstemmed Development of Electric Vehicle Charging Corridor for South Carolina
title_short Development of Electric Vehicle Charging Corridor for South Carolina
title_sort development of electric vehicle charging corridor for south carolina
topic Electric vehicle
Charging station
Combinatorial optimization
Heuristics
url http://www.sciencedirect.com/science/article/pii/S2046043016301708
work_keys_str_mv AT shengyinliphdcandidate developmentofelectricvehiclechargingcorridorforsouthcarolina