Placement of Loading Stations for Electric Vehicles: No Detours Necessary!

Funke, Stefan; Nusser, André; Storandt, Sabine

doi:10.1613/jair.4688

Cited by 28 publications

(29 citation statements)

References 11 publications

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“…There is a need to identify reasonable locations for the CS with few instances as possible so the EVs can achieve reachability and connectivity in the network [11]. The authors of [14] say that EVs will only prevail if a road trip with an EV can be undertaken without taking no significant detour from the current paths. So, this study proposed a way to solve the problem of placement of the CS in a way that for every shortest path there are enough CS, meaning that the EV will not get stranded when starting with a fully loaded battery, called EV Shortest Path Cover.…”

Section: Comparison To Forecasting In Open Car Parksmentioning

confidence: 99%

“…A variant of placing CS in the network is proposed in [16], while taking into account the reasonability of routes and sparsity of the CS set, with the goal of placing CS in certain locations where the EV drivers do not need to leave the shortest path trips and make large detours for recharging. So a new and more practical model for placing CS for EVs is proposed, but with a larger complexity.…”

Section: Comparison To Forecasting In Open Car Parksmentioning

confidence: 99%

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Electric Vehicle Charging Process and Parking Guidance App

2019

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This research work presents an information system to handle the problem of real-time guidance towards free charging slot in a city using past date and prediction and collaborative algorithms since there is no real-time system available to provide information if a charging spot is free or occupied. We explore the prediction approach using past data correlated with weather conditions. This approach will help the driver in the daily use of his electric vehicle, minimizing the problem of range anxiety, provide guidance towards charging spots with a probability value of being available for charging in a context for the app and smart cities. This work handles the uncertainty of the drivers to get a suitable and vacant place at a charging station because missing real-time information from the system and also during the driving process towards the free charging spot can be taken. We introduce a framework to allow collaboration and prediction process using past related data.

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Section: Comparison To Forecasting In Open Car Parksmentioning

confidence: 99%

Section: Comparison To Forecasting In Open Car Parksmentioning

confidence: 99%

Electric Vehicle Charging Process and Parking Guidance App

2019

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“…In the past few years, the problem of locating charging stations for electric vehicles has attracted considerable attention. For instance, efficient solution approaches based on new MILP formulations were proposed in [2] and [20] while heuristic solution techniques for large-scale problems were studied in [5] and [6]. Extensions of the basic problem taking into account a limited charging capacity of the stations (see e.g.…”

Section: Position In the Literaturementioning

confidence: 99%

Efficient solution approaches for locating electric vehicle fast charging stations under driving range uncertainty

Boujelben

Gicquel

2019

Computers & Operations Research

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We seek to determine the best locations for electric vehicle fast charging stations under driving range uncertainty. Two stochastic programming based models have been recently proposed to handle the resulting stochastic flow refueling location problem: a first one maximizing the expected flow coverage of the network, a second one based on joint chance constraints. However, significant computational difficulties were encountered while solving large-size instances. We thus propose two efficient solution approaches for this problem. The first one is based on a new location-allocation type model for this problem and results in a MILP formulation, while the second one is a tabu search heuristic. Our numerical experiments show that when using the proposed MILP formulation, the computation time needed to provide guaranteed optimal solutions is significantly reduced as compared to the one needed when using the previously published MILP formulation. Moreover, our results also show that the tabu search method consistently provides good quality solutions within short computation times.

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“…[18][19][20] To enable mobility of EVs, models of the placement of least charging stations on the shortest path are proposed to avoid detours for charging. 21,22 A conceptual optimization model is proposed to analyse travel by EVs along a long corridor. The objective is to select the battery size and charging capacity (in terms of charging power at each station and the number of stations needed along the corridor) to meet a given level of service in such a way that the total social cost is minimized.…”

Section: Charging Station Design and Location Studiesmentioning

confidence: 99%

Electric vehicles: A review of network modelling and future research needs

Jing

Yan

Kim

et al. 2016

Advances in Mechanical Engineering

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Electric vehicles are believed to be an effective solution for reducing greenhouse gas emissions. Despite extensive study on the attributes and characteristics of electric vehicles and their charging infrastructure design, the development and network modelling of electric vehicles are still evolving and limited. This article provides a comprehensive review of electric vehicle studies and identifies existing research gaps in the aspects of theories, modelling approaches, solution algorithms and applications. This article first describes the electric vehicles' concepts, market share, characteristics and charging infrastructures. Then, the studies on traffic assignment problem with electric vehicles in the network and limited charging facilities are particularly discussed. We conclude that it is of great importance to take into account electric vehicles' special characteristics (e.g. range limit) in predicting their routing behaviour and charging infrastructure design networks.

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Placement of Loading Stations for Electric Vehicles: No Detours Necessary!

Cited by 28 publications

References 11 publications

Electric Vehicle Charging Process and Parking Guidance App

Electric Vehicle Charging Process and Parking Guidance App

Efficient solution approaches for locating electric vehicle fast charging stations under driving range uncertainty

Electric vehicles: A review of network modelling and future research needs

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