Efficient Assignment of Electric Vehicles to Charging Stations

Elghitani, Fadi; El-Saadany, Ehab F.

doi:10.1109/tsg.2020.3016476

Cited by 42 publications

(9 citation statements)

References 24 publications

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“…The proof of Theorem 1: (18) is gradually decomposed into segments to derive (24). From ( 18) and ( 20), we can write that: The proof of Theorem 2: (19) is gradually decomposed into segments to derive (25). From ( 19) and ( 20…”

Section: Appendix Amentioning

confidence: 99%

“…Results show that the charging efficiency and charging convenience in terms of waiting and trip times have improved. Elghitani et al [19] proposed a useroriented method with a queueing model for the assignment of EVs to charging stations. It considers the average time spent by the EV user from requesting the charging service to accessing it as the performance indicator.…”

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confidence: 99%

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A Hybrid Power Heronian Function-Based Multicriteria Decision-Making Model for Workplace Charging Scheduling Algorithms

Erdoğan

Pamučar

Kucuksari

et al. 2023

IEEE Trans. Transp. Electrific.

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Section: Appendix Amentioning

confidence: 99%

mentioning

confidence: 99%

A Hybrid Power Heronian Function-Based Multicriteria Decision-Making Model for Workplace Charging Scheduling Algorithms

Erdoğan

Pamučar

Kucuksari

et al. 2023

IEEE Trans. Transp. Electrific.

View full text Add to dashboard Cite

“…[51] adopted an expanded transportation network model to describe transportation constraints and the AC power flow model to describe electrical constraints and proposed a second order cone programming model to minimize the total social cost that includes driving and charging time costs of PEV drivers and power supply costs. Some studies considered a Charging Network Operator (CNO)'s perspective [9,26,27] where the EV owners cannot directly choose the charging station but are rather assigned to certain stations by a central controller based on the optimization objectives. In this setting, users can specify their desired SoC and their destinations to the CNO and the CNO will assign each EV to an optimal charging station based on the charging request.…”

Section: Grid-to-vehicle (G2v) 21 Operation Of a Single Charging Stationmentioning

confidence: 99%

“…In this setting, users can specify their desired SoC and their destinations to the CNO and the CNO will assign each EV to an optimal charging station based on the charging request. Specifically, [9] developed an EV assignment algorithm based on the Lyapunov optimization method that aims to minimize the average time spent from requesting the service to accessing it. [26] formulated an integer multi-objective optimization problem for optimal coordination of a fleet of cooperative EVs considering the objectives of EV owners, charging station owners, and power systems.…”

Section: Grid-to-vehicle (G2v) 21 Operation Of a Single Charging Stationmentioning

confidence: 99%

A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms

Tang

Sun

et al. 2022

Preprint

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The rapid growth of electric vehicles (EVs) has promised a next-generation transportation system with reduced carbon emission. The fast development of EVs and charging facilities is driving the evolution of Internet of Vehicles (IoV) to Internet of Electric Vehicles (IoEV). IoEV benefits from both smart grid and Internet of Things (IoT) technologies which provide advanced bi-directional charging services and real-time data processing capability, respectively. The major design challenges of the IoEV charging control lie in the randomness of charging events and the mobility of EVs. In this article, we present a holistic review on advanced bi-directional EV charging control algorithms. For Grid-to-Vehicle (G2V), we introduce the charging control problem in two scenarios: 1) Operation of a single charging station and 2) Operation of multiple charging stations in coupled transportation and power networks. For Vehicle-to-Grid (V2G), we discuss how EVs can perform energy trading in the electricity market and provide ancillary services to the power grid. Besides, a case study is provided to illustrate the economic benefit of the joint optimization of routing and charging scheduling of multiple EVs in the IoEV. Last but not the least, we will highlight some open problems and future research directions of charging scheduling problems for IoEVs.CCS Concepts: • General and reference → Surveys and overviews.

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“…The battery charging time is significantly longer than the refuelling time of a conventional car [ 3 ]. Charging times range from tens of minutes to tens of hours, depending on the specific vehicle type, the battery itself and the charging station [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Innovative Bidirectional Isolated High-Power Density On-Board Charge for Vehicle-to-Grid

Hrbáč

Hrdina

Kolář

et al. 2022

Sensors

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This paper deals with developing and implementing a bidirectional galvanically isolated on-board charger of a high-power density. The power density of the new charger was 4 kW/kg and 2.46 kW/dm3, and the maximum efficiency was 96.4% at 3.4 kW. Due to the requirement to achieve a high-power density, a single-stage inverter topology was used. Regarding switching losses, due to the topology of the circuit with so-called hard switching, the switching frequency was set to 150 kHz. A laboratory prototype was built to verify the properties and operating principles of the described charger topology. The on-board charger has been tested in a microgrid test platform. Due to the parasitic properties of the transformer and other electronic components, overvoltage with subsequent oscillations occurred on the primary side of the transformer and damped resonance on its secondary side. These parasitic properties caused interference and especially voltage stress on the semiconductor elements. These undesirable phenomena have been eliminated by adding an active element to the charger topology and a new transistor control strategy. This new switching control strategy of transistors has been patented.

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Efficient Assignment of Electric Vehicles to Charging Stations

Cited by 42 publications

References 24 publications

A Hybrid Power Heronian Function-Based Multicriteria Decision-Making Model for Workplace Charging Scheduling Algorithms

A Hybrid Power Heronian Function-Based Multicriteria Decision-Making Model for Workplace Charging Scheduling Algorithms

A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms

Innovative Bidirectional Isolated High-Power Density On-Board Charge for Vehicle-to-Grid

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