Willing to participate in vehicle-to-grid (V2G)? Why not!

Geske, Joachim; Schumann, Diana

doi:10.1016/j.enpol.2018.05.004

Cited by 134 publications

(65 citation statements)

References 24 publications

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“…First of all, because it aims to reduce pollution and to achieve a greater energy efficiency. According to the results of survey presented in [77], willingness for participation of EVs drivers in V2G projects might also grow as problems with 'range anxiety' and the 'minimum allowed range' are solved.…”

Section: VIIImentioning

confidence: 99%

Electric Vehicles as Electricity Storages in Electric Power Systems

Popović

Jereb

Kilibarda

et al. 2018

Logistics &Amp; Sustainable Transport

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Improvements in battery technology make electric vehicles more and more suitable for the use as electricity storages. Many benefits could be achieved by using electric vehicles for storing electricity in their batteries. This paper talks about the idea of electric vehicles as electricity storages in electric power systems. The idea has a great number of supporters, but also a significant part of the professional community believes that is unfeasible. This paper is not classified in either side and strives to give a realistic picture of this idea. For this purpose, findings from papers published in scientific journals are mainly used. There is also some information from websites, mainly for some technical issues. Partly, the opinions of the authors are present. Specificities of EVs and EPSs that enabled the birth of this idea are explained along with proposed concepts through which the idea can be implemented. Keeping with the vehicle to grid concept, issues about the implementation of the idea are considered. Achievements in the practical realization of the idea are also presented.

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Section: VIIImentioning

confidence: 99%

Electric Vehicles as Electricity Storages in Electric Power Systems

Popović

Jereb

Kilibarda

et al. 2018

Logistics &Amp; Sustainable Transport

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“…The power flow is generally managed by a socalled aggregator, which arbitrates between the needs of EVs and the Grid (ensuring a net flow of energy to the EV battery pack to recharge it for driving purposes). A V2G network needs to serve both the grid and the connected EVs sufficiently to a) fulfil the designated grid service provided, and b) to battle potential range anxiety from EV owners and encourage participation in V2G schemes [10].…”

Section: Introductionmentioning

confidence: 99%

Multi-Layer Event-Based Vehicle-to-Grid (V2G) Scheduling With Short Term Predictive Capability Within a Modular Aggregator Control Structure

Krueger

Cruden

2020

IEEE Trans. Veh. Technol.

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In this work a novel method of event-based V2G scheduling is devised that is suitable for dynamic real time aggregator control in large scale V2G applications within centrally controlled EV car parks. The method is applicable in deterministic systems where a V2G network provides or receives electricity in reoccurring and predictable patterns (events). The scheduling strategy shown is based on a robust modular high-level aggregator control structure and a proposed communications and data management system. The scheduling consists of three algorithm layers, differentiating between predictive scheduling for in-event periods, smart charging for out-of-event periods and reactive scheduling for ongoing adjustments in real-time to account for uncertainty. The scheduling process is described in terms of its underlying rules for prioritising EVs to be either charged or discharged. It's behaviour is then analysed using a simulated car park of up to one thousand connected EVs for an example application in which a V2G network is used to support nearby electrified rail infrastructure, providing power for train acceleration and accepting power from regenerative braking. The departure or arrival of a train of known type and speed pattern can be regarded as a reoccurring event and its effect on the V2G network is therefore predictable due to train schedules and tracking.

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“…Many factors will influence a user's decision to make their vehicle available to participate in a V2G event, such as vehicle availability, reward opportunities and vehicle use (Gough et al 2017;Geske and Schumann 2018;Will and Schuller 2016;Noel et al 2018) and a successful service must therefore learn the key drivers of individual user decisions to help refine and optimise the operation of the overall system. This is particularly apparent for services that seek to recruit individual electric vehicle owners rather than fleets of vehicles, which are typically more predictable.…”

Section: Introductionmentioning

confidence: 99%

Learning capacity: predicting user decisions for vehicle-to-grid services

et al. 2019

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The electric vehicles (EV) market is projected to continue its rapid growth, which will profoundly impact the demand on the electricity network requiring costly network reinforcements unless EV charging is properly managed. However, as well as importing electricity from the grid, EVs also have the potential to export electricity through vehicle-togrid (V2G) technology, which can help balance supply and demand and stabilise the grid through participation in flexibility markets. Such a scenario requires a population of EVs to be pooled to provide a larger storage resource. Key to doing so effectively however is knowledge of the users, as they ultimately determine the availability of a vehicle. In this paper we introduce a machine learning model that aims to learn both a) the criteria influencing users when they decided whether to make their vehicle available and b) their reliability in following through on those decisions, with a view to more accurately predicting total available capacity from the pool of vehicles at a given time. Using a series of simplified simulations, we demonstrate that the learning model is able to adapt to both these factors, which allows the required capacity of a market event to be satisfied more reliably and using a smaller number of vehicles than would otherwise be the case. This in turn has the potential to support participation in larger and more numerous market events for the same user base and use of the technology for smaller groups of users such as individual communities.

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Willing to participate in vehicle-to-grid (V2G)? Why not!

Cited by 134 publications

References 24 publications

Electric Vehicles as Electricity Storages in Electric Power Systems

Electric Vehicles as Electricity Storages in Electric Power Systems

Multi-Layer Event-Based Vehicle-to-Grid (V2G) Scheduling With Short Term Predictive Capability Within a Modular Aggregator Control Structure

Learning capacity: predicting user decisions for vehicle-to-grid services

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