Estimation of cost savings from participation of electric vehicles in vehicle to grid (V2G) schemes

Kiaee, Mahdi; Cruden, Andrew; Sharkh, Suleiman M.

doi:10.1007/s40565-015-0130-2

Cited by 40 publications

(15 citation statements)

References 19 publications

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“…half of the vehicles (52%) would cost more (in charging) than they would earn (in revenues) [75]. Another study using empirical electricity market data from Germany warned that, 'simply selling energy to [P]EV owners results in substantially higher revenues than ancillary services such as frequency regulation… The times at which vehicles enter and leave garages follow stochastic processes and even if the chance is slim, the number of vehicles may be insufficient to supply the required amount of power at the time of a regulation incident [76].'…”

Section: Financing and Business Modelsmentioning

confidence: 99%

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Sovacool

Noel

Axsen

et al. 2018

Environ. Res. Lett.

170

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Vehicle-to-grid (V2G) refers to efforts to bi-directionally link the electric power system and the transportation system in ways that can improve the sustainability and security of both. A transition to V2G could enable vehicles to simultaneously improve the efficiency (and profitability) of electricity grids, reduce greenhouse gas emissions for transport, accommodate low-carbon sources of energy, and reap cost savings for owners, drivers, and other users. To understand the recent state of this field of research, here we conduct a systematic review of 197 peer-reviewed articles published on V2G from 2015 to early 2017. We find that the majority of V2G studies in that time period focus on technical aspects of V2G, notably renewable energy storage, batteries, or load balancing to minimize electricity costs, in some cases including environmental goals as constraints. A much lower proportion of studies focus on the importance of assessing environmental and climate attributes of a V2G transition, or on the role of consumer acceptance and knowledge of V2G systems. Further, there is need for exploratory work on natural resource use and externalities, discourses and narratives as well as social justice, gender, and urban resilience considerations. These research gaps need to be addressed if V2G is to achieve the societal transition its advocates seek.

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Section: Financing and Business Modelsmentioning

confidence: 99%

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Sovacool

Noel

Axsen

et al. 2018

Environ. Res. Lett.

170

View full text Add to dashboard Cite

show abstract

“…Prosumagers may make the most of storage devices to use their self-produced energy in periods of no PV availability or peak grid prices, thus minimizing costs. These systems can also be used to store energy purchased from retailers or other prosumers during low pricing periods, to be self-consumed later, providing an extra source of demand flexibility [25].…”

Section: The Role Of Energy Communities In the Eu Agendamentioning

confidence: 99%

Assessing the Influence of Different Goals in Energy Communities’ Self-Sufficiency—An Optimized Multiagent Approach

et al. 2021

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Understanding to what extent the emergence of prosumers and prosumagers organized in energy communities can impact the organization and operation of power grids has been one of the major recent research avenues at the European level. In renewable-based communities aiming to reach some level of energy self-sufficiency, a key issue to be addressed is assessing how the presence of end-users playing different roles in the system (self-consuming, producing and trading, performing demand management, etc.) can influence the overall system performance. In this setting, this paper combines Distributed Artificial Intelligence and optimization approaches to assess how prosumagers and consumers pursuing different goals can influence the energy self-sufficiency of a local energy community. The residential demand is accurately modeled, and the agents’ preferences are considered in the modeling to represent a smart community. The results show that although energy community members may have conflicting individual goals, the overall system self-sufficiency can be maximized with economic benefits for all stakeholders, thus illustrating the advantages of energy communities.

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Section: Test Casementioning

confidence: 99%

“…The normal distribution function is used to model the forecasting errors as shown in Figure 2 [27]. Here, one segment is centered as the predicted mean that is extracted from [30] and two slices are created to forecast errors with standard deviation and the initial EVs' demand supplied by all aggregators is generated randomly. The maximum limitation for positive balancing energy is equal to the maximum rate of charging for each EV battery that is 3.6 kWh.…”

Section: Test Casementioning

confidence: 99%

A Stochastic Bi-Level Scheduling Approach for the Participation of EV Aggregators in Competitive Electricity Markets

et al. 2017

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This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggregator in a competitive environment. In this approach, the EV aggregator decides to participate in day-ahead (DA) and balancing markets, and provides energy price offers to the EV owners in order to maximize its expected profit. Moreover, from the EV owners' viewpoint, energy procurement cost of their EVs should be minimized in an uncertain environment. In this study, the sources of uncertainty-including the EVs demand, DA and balancing prices and selling prices offered by rival aggregators-are modeled via stochastic programming. Therefore, a two-level problem is formulated here, in which the aggregator makes decisions in the upper level and the EV clients purchase energy to charge their EVs in the lower level. Then the obtained nonlinear bi-level framework is transformed into a single-level model using Karush-Kuhn-Tucker (KKT) optimality conditions. Strong duality is also applied to the problem to linearize the bilinear products. To deal with the unwilling effects of uncertain resources, a risk measurement is also applied in the proposed formulation. The performance of the proposed framework is assessed in a realistic case study and the results show that the proposed model would be effective for an EV aggregator decision-making problem in a competitive environment.

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Estimation of cost savings from participation of electric vehicles in vehicle to grid (V2G) schemes

Cited by 40 publications

References 19 publications

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Assessing the Influence of Different Goals in Energy Communities’ Self-Sufficiency—An Optimized Multiagent Approach

A Stochastic Bi-Level Scheduling Approach for the Participation of EV Aggregators in Competitive Electricity Markets

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