An optimal charging station location model with the consideration of electric vehicle’s driving range

He, Jia; Yang, Hai; Tang, Tie-Qiao; Huang, Hai-Jun

doi:10.1016/j.trc.2017.11.026

Cited by 248 publications

(77 citation statements)

References 37 publications

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“…To produce the right answer to the question at hand, a flow-capturing problem must be formulated in accordance with the objective and constraints of the study. If there is a constraint on the number of charging stations that can be allocated, the maximal coverage approach may be used [16,[22][23][24][25][26]. In this approach, the objective is set to allocate a given number of charging stations so as to maximize the flows captured.…”

Section: Methodologies Typically Applied In Researchmentioning

confidence: 99%

Location-Allocation of Electric Vehicle Fast Chargers—Research and Practice

Motoaki

2019

WEVJ

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This paper conducts a comparative analysis of academic research on location-allocation of electric vehicle fast chargers into the pattern of the actual fast-charger allocation in the United States. The work aims to highlight the gap between academic research and actual practice of charging-station placement and operation. It presents evidence that the node-serving approach is, in fact, applied in the actual location-allocation of fast charging stations. However, little evidence suggests that flow-capturing, which has been much more predominantly applied in research, is being applied in practice. The author argues that a large-scale location-allocation plan for public fast chargers should be formulated based on explicit consideration of stakeholders, the objective, practical constraints, and underlining assumptions.

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Section: Methodologies Typically Applied In Researchmentioning

confidence: 99%

Location-Allocation of Electric Vehicle Fast Chargers—Research and Practice

Motoaki

2019

WEVJ

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“…The reasonable placement and the cost of charging infrastructure are not only important for charging convenience but are also crucial to network charging efficiency which has a potential impact on future investment. In the paper of He et al [157], a double-level programming model was suggested to find the best charging station placement by taking the driving range of EVs in to account. Tang et al [158].…”

Section: The Challenges Of Charging Networkmentioning

confidence: 99%

Technology Development of Electric Vehicles: A Review

et al. 2019

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To reduce the dependence on oil and environmental pollution, the development of electric vehicles has been accelerated in many countries. The implementation of EVs, especially battery electric vehicles, is considered a solution to the energy crisis and environmental issues. This paper provides a comprehensive review of the technical development of EVs and emerging technologies for their future application. Key technologies regarding batteries, charging technology, electric motors and control, and charging infrastructure of EVs are summarized. This paper also highlights the technical challenges and emerging technologies for the improvement of efficiency, reliability, and safety of EVs in the coming stages as another contribution.

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“…Kweon et al [39] extend the approach suggested in Ventura et al [38] to locate a refueling station anywhere along a tree network to the case where a portion of drivers are willing to deviate to receive refueling service. He et al [40] propose a bilevel model to solve the optimal locations of electric charging stations, through taking the driving range limitation of an electric vehicle, the battery charging time required, and the situation in which some electric vehicle drivers possibly charge at home into account. While Kuby and Lim [30] and the following studies solve the AF refueling station location problem using a maximal covering location problem, Wang and Lin [41] solve this problem using a set-covering model with the objective of minimizing the total cost of locating stations to cover all the traffic flow on a given transportation network.…”

Section: Main Distinctions Of Our Research Workmentioning

confidence: 99%

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

Hwang

Kweon

Ventura

2020

Journal of Advanced Transportation

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With the development of alternative fuel (AF) vehicle technologies, studies on finding the potential location of AF refueling stations in transportation networks have received considerable attention. Due to the strong limited driving range, AF vehicles for long-distance intercity trips may require multiple refueling stops at different locations on the way to their destination, which makes the AF refueling station location problem more challenging. In this paper, we consider that AF vehicles requiring multiple refueling stops at different locations during their long-distance intercity trips are capable of making detours from their preplanned paths and selecting return paths that may be different from original paths for their round trips whenever AF refueling stations are not available along the preplanned paths. These options mostly need to be considered when an AF refueling infrastructure is not fully developed on a highway system. To this end, we first propose an algorithm to generate alternative paths that may provide the multiple AF refueling stops between all origin/destination (OD) vertices. Then, a new mixed-integer programming model is proposed to locate AF refueling stations within a preselected set of candidate sites on a directed transportation network by maximizing the coverage of traffic flows along multiple paths. We first test our mathematical model with the proposed algorithm on a classical 25-vertex network with 25 candidate sites through various scenarios that consider a different number of paths for each OD pair, deviation factors, and limited driving ranges of vehicles. Then, we apply our proposed model to locate liquefied natural gas refueling stations in the state of Pennsylvania considering the construction budget. Our results show that the number of alternative paths and deviation distance available significantly affect the coverage of traffic flows at the stations as well as computational time.

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An optimal charging station location model with the consideration of electric vehicle’s driving range

Cited by 248 publications

References 37 publications

Location-Allocation of Electric Vehicle Fast Chargers—Research and Practice

Location-Allocation of Electric Vehicle Fast Chargers—Research and Practice

Technology Development of Electric Vehicles: A Review

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

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