A Review of Charge Scheduling of Electric Vehicles in Smart Grid

This study focuses on the potential role of plugin electric vehicles (PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid (V2G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2G process is first formulated as an optimal control problem. Then, a two-stage V2G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm.

show abstract

“…V2G can be implemented in two different control architectures, namely, centralized and decentralized controls [15], as shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system

Erdoğan

Erden

Kisacikoglu

2018

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

show abstract

“…E LECTRIC Vehicles (EVs) [1] are expected to be widely adopted as individual, commercial, and public vehicle fleets. However, compared with traditional gasoline-powered vehicles, EVs are more likely to run out of energy, thus should be charged during their journeys.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, how to manage the charging processes of EVs to improve their drivers' comfort, is a vital research issue for the success and long-term viability of EV industry. Majority of previous works investigate "charging scheduling" [1] (concerning when/whether to charge) where EVs have already been parked at homes/Charging Stations (CSs). In contrary, we address "CS-selection" (concerning where to charge) that has not been adequately investigated.…”

Section: Introductionmentioning

confidence: 99%

Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service

Cao

Wang

Zhang

et al. 2019

IEEE Systems Journal

View full text Add to dashboard Cite

Abstract-Electro-Mobility has become an increasingly important research problem in urban city. Due to the limited electricity of battery, Electric Vehicle (EV) drivers may experience discomfort for long charging waiting time. Different from plug-in charging technology, we investigate the battery switch technology to improve EV drivers' comfort (e.g., reduce the service waiting time from tens of minutes to a few minutes), by benefiting from switchable (fully-recharged) batteries cycled at Charging Stations (CSs). Since demand hotspot may still happen at CSs (e.g., running out of switchable batteries), incoming EVs may wait additional time to get their battery switched, and thus the EV driver's comfort is degraded. Firstly, we propose a centralized reservation enabling service, considering EVs' reservations (including arrival time, expected charging time of their batteries to be depleted) to optimally coordinate their battery switch plans. Secondly, a decentralized system is further proposed, by facilitating the Vehicle-to-Vehicle (V2V) anycasting to deliver EV's reservations. This helps to address some of the privacy issues that can be materialized in centralized system and reduce communication cost (e.g., through cellular network for reservation making). Results under the Helsinki city scenario show a trade-off between comparable performance (e.g., service waiting time, number of switched batteries) and cellular network cost for EVs' reservations delivery.

show abstract

“…In order to achieve this, the vehicle and charging station communicate with each other for the reservation of slots according to the availability and the cost functions [20]. The progress in EVs in the near future is expected to be high and must be supported with the help of available and future communication systems [23][24][25][26][27]. The proposed real-time EV charge scheduling depends upon the battery dynamics and availability of charging slots.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Forecasting of EV Charging Station Scheduling for Smart Energy Systems

Bharatiraja¹,

Padmanaban²,

Siano³

et al. 2017

Preprint

View full text Add to dashboard Cite

Abstract:The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate users' "range anxiety". The existing charging stations fail to adopt power provision allocation and scheduling management. To improve the existing charging infrastructure data based on real-time information and availability of reserves at charging stations could be uploaded to the users to help them locate the nearest charging station for an EV. This research article focuses on an a interactive user application developed through SQL and PHP platform to allocate the charging slots based on estimated battery parameters, which uses data communication with charging stations to receive the slot availability information. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on road due to battery drain out. The proposed model is implemented using a low-cost microcontroller and the system etiquette tested.

show abstract

A Review of Charge Scheduling of Electric Vehicles in Smart Grid

Cited by 312 publications

References 63 publications

A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system

A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system

Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service

Real-Time Forecasting of EV Charging Station Scheduling for Smart Energy Systems

Contact Info

Product

Resources

About