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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doaj-3869bcb2025c4251a109e49fc31b997b2020-11-24T23:24:32ZengElsevierInternational 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 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shengyin Li, Ph.D. candidate |
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 |
author_facet |
Shengyin Li, Ph.D. candidate |
author_sort |
Shengyin Li, Ph.D. candidate |
title |
Development of Electric Vehicle Charging Corridor for South Carolina |
title_short |
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_sort |
development of electric vehicle charging corridor for south carolina |
publisher |
Elsevier |
series |
International Journal of Transportation Science and Technology |
issn |
2046-0430 |
publishDate |
2015-01-01 |
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. |
topic |
Electric vehicle Charging station Combinatorial optimization Heuristics |
url |
http://www.sciencedirect.com/science/article/pii/S2046043016301708 |
work_keys_str_mv |
AT shengyinliphdcandidate developmentofelectricvehiclechargingcorridorforsouthcarolina |
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