The battery charging station location problem: Impact of users’ range anxiety and distance convenience

Guo, Fang; Yang, Jun; Lu, Jianyi

doi:10.1016/j.tre.2018.03.014

Cited by 165 publications

(55 citation statements)

References 47 publications

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“…identified important parameters that affect the optimal location of EV charging stations by establishing a non-deterministic polynomial model and applying a simulation algorithm Due to the critical role of infrastructure in supporting EV penetration, Zhou [159] has analyzed some important factors affecting the regulation of charging stations. To reduce obstacles in the adoption of EVs, such as range anxiety and distance deviations, Guo et al [160] applied an adaptive search and k-shortest path algorithm.…”

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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Section: The Challenges Of Charging Networkmentioning

confidence: 99%

Technology Development of Electric Vehicles: A Review

et al. 2019

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“…Range anxiety importance has also been shown in computational studies that discussed its relationship with the CS network. In the work by Guo et al [30], the battery charging station location problem was addressed where range anxiety and distance convenience were taken into account. While the KSIGALNS algorithm that they developed to solve their bi-level integer programming model was proven to be very effective compared to standard and previous solutions approaches, the analysis of range anxiety as a parameter shows that it is an essential factor to the location strategy of the CS network.…”

Section: Literature Reviewmentioning

confidence: 99%

A Method for the Optimization of Daily Activity Chains Including Electric Vehicles

Rizopoulos

Esztergár-Kiss

2020

Energies

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The focus of this article is to introduce a method for the optimization of daily activity chains of travelers who use Electric Vehicles (EVs) in an urban environment. An approach has been developed based on activity-based modeling and the Genetic Algorithm (GA) framework to calculate a suitable schedule of activities, taking into account the locations of activities, modes of transport, and the time of attendance to each activity. The priorities of the travelers concerning the spatial and temporal flexibility were considered, as well as the constraints that are related to the limited range of the EVs, the availability of Charging Stations (CS), and the elevation of the road network. In order to model real travel behavior, two charging scenarios were realized. In the first case, the traveler stays in the EV at the CS, and in the second case, the traveler leaves the EV to charge at the CS while conducting another activity at a nearby location. Through a series of tests on synthetic activity chain data, we proved the suitability of the method elaborated for addressing the needs of travelers and being utilized as an optimization method for a modern Intelligent Transportation System (ITS).

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“…The literature on EV charging stations has conventionally postulated that large scale systems of public EV charging stations will be required in the future [2][3][4][5][6][7].…”

Section: Location-allocation Of Ev Fast Chargersmentioning

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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The battery charging station location problem: Impact of users’ range anxiety and distance convenience

Cited by 165 publications

References 47 publications

Technology Development of Electric Vehicles: A Review

Technology Development of Electric Vehicles: A Review

A Method for the Optimization of Daily Activity Chains Including Electric Vehicles

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

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