Electric vehicle fleet integration in the danish EDISON project - A virtual power plant on the island of Bornholm

Binding, Carl; Gantenbein, Dieter; Jansen, Bernard J.; Sundström, Olle; Andersen, Peter Bach; Marra, Francesco; Poulsen, Bjarne; Træholt, Chresten

doi:10.1109/pes.2010.5589605

Cited by 92 publications

(50 citation statements)

References 19 publications

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“…In the present case study, the goal is to build an operator who could be considered from the grid manager point of view as a single actor, to some extend similar to a virtual power plant (VPP). Indeed, managing an EV fleet into a VPP has been experimented by Binding et al [10].…”

Section: Description Of the Collaborative Systemmentioning

confidence: 99%

Stochastic optimization of an Electric Vehicle Fleet Charging with Uncertain Photovoltaic Production

Latimier

Multon

Ahmed

et al. 2015

2015 International Conference on Renewable Energy Research and Applications (ICRERA)

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Abstract-Simultaneous development of photovoltaic generation and electric vehicles strengthens the solicitations on the electric power system. This paper investigates the possible synergy between these players to jointly improve the production predictability while ensuring a low carbon mobility. It stands for a step towards a quantification of its economic and environmental fallout. First a context is described for a PV-EV collaboration. Then this is gathered into an optimization problem. Grid commitment constraints, battery aging and mobility needs are here considered from the environmental point of view of equivalent primary energy. Finally, a resolution method is presented which achieve an time-efficient optimization of the power flow for each vehicle, based on upstream computed charging policies. It relies on a stochastic modeling of both vehicles availability and forecast error of the PV production. The resolution framework is the stochastic dynamic programming, coupled with on-line minimization so as to avoid the curse of dimensionality. The proposed resolution enables to compute optimal power flow for each vehicle, even among large fleets. The emphasis is here set on a versatile resolution method which could take over many detailed objective functions.

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Section: Description Of the Collaborative Systemmentioning

confidence: 99%

Stochastic optimization of an Electric Vehicle Fleet Charging with Uncertain Photovoltaic Production

Latimier

Multon

Ahmed

et al. 2015

2015 International Conference on Renewable Energy Research and Applications (ICRERA)

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“…Meeting these conditions thus requires hundreds to thousands of EVs aggregated to an Electric Vehicle Virtual Power Plant (EV-VPP) [5,13]. This is done by an aggregator who serves as a mediator between the EV owners and the electricity market.…”

Section: The V2g Conceptmentioning

confidence: 99%

“…This concept termed Vehicle-to-Grid (V2G) was first mentioned in 1997 [2] and has been subject to intensive research in the last two decades. In this context, various theoretical investigations confirmed its effectiveness to improve power grid stability [1,3e7] and several fully functional prototypes where implemented [5,6,8].…”

Section: Introductionmentioning

confidence: 96%

A price-responsive dispatching strategy for Vehicle-to-Grid: An economic evaluation applied to the case of Singapore

Pelzer¹,

Ciechanowicz²,

Aydt³

et al. 2014

Journal of Power Sources

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A charging and dispatching strategy for optimizing profits from V2G is presented. This optimization strategy builds on temporally resolved electricity market data. A case study shows that this method turns a S$ 1000 annual loss into a S$ 130 profit. Sensitivity analyses indicate potential for further increase of profitability. Employing this strategy in other countries is assumed to yield much greater profits. a r t i c l e i n f o b s t r a c tEmploying electric vehicles as short-term energy storage could improve power system stability and at the same time create a new income source for vehicle owners. In this paper, the economic viability of this concept referred to as Vehicle-to-Grid is investigated. For this purpose, a price-responsive charging and dispatching strategy built upon temporally resolved electricity market data is presented. This concept allows vehicle owners to maximize returns by restricting market participation to profitable time periods. As a case study, this strategy is then applied using the example of Singapore. It is shown that an annual loss of S$ 1000 resulting from a non-price-responsive strategy as employed in previous works can be turned into a S$ 130 profit by applying the price-responsive approach. In addition to this scenario, realistic mobility patterns which restrict the temporal availability of vehicles are considered. In this case, profits in the range of S$ 21eS$ 121 are achievable. Returns in this order of magnitude are not expected to make Vehicle-to-Grid a viable business case, sensitivity analyses, however, show that improved technical parameters could increase profitability. It is further assumed that employing the priceresponsive strategy to other national markets may yield significantly greater returns.

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“…The aggregation of electric vehicles (EVs) becomes an attractive alternative solution to encourage the participation of the groups of EVs to the electricity markets. The recent research shows the feasibility of the EV's participation in the markets [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Stochastic Charging Coordination Method for Electric Vehicle (EV) Aggregator Considering Uncertainty in EV Departures

Kim¹,

Kong²,

Joo³

2016

Journal of Electrical Engineering and Technology

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-This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.

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Electric vehicle fleet integration in the danish EDISON project - A virtual power plant on the island of Bornholm

Cited by 92 publications

References 19 publications

Stochastic optimization of an Electric Vehicle Fleet Charging with Uncertain Photovoltaic Production

Stochastic optimization of an Electric Vehicle Fleet Charging with Uncertain Photovoltaic Production

A price-responsive dispatching strategy for Vehicle-to-Grid: An economic evaluation applied to the case of Singapore

Stochastic Charging Coordination Method for Electric Vehicle (EV) Aggregator Considering Uncertainty in EV Departures

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