Optimal Charging Strategies for Unidirectional Vehicle-to-Grid

Sortomme, E.; El-Sharkawi, M.A.

doi:10.1109/tsg.2010.2090910

Cited by 648 publications

(405 citation statements)

References 16 publications

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“…The term POP itself comes from ancillary services markets. It represents the average level of operation for a market participant providing regulation services [10]. It is assumed that the EV aggregator can deviate from the dayahead power-drawn (or POP) to balance energy by reducing or increasing their charging rate with consideration of EV aggregator energy constraints .…”

Section: Market Framworkmentioning

confidence: 99%

“…The lower-level problem (10)-(15) represents the day-ahead market clearing with the aim of maximization of social welfare given by (10) The primal variables of the lower-level problem (10) are those in set , and its dual variables are represented by the set which are indicated at the corresponding constraints following a colon.…”

Section: (9)mentioning

confidence: 99%

“…It is vital for producers and market operator to review equilibrium analysis to investigate the sensitivity analysis of diverse parameters on the expected profit, social welfare, and active players in vehicle-to-grid (V2G) markets [6][7][8]. A mechanism is necessary to integrate the electrified transportation within the power system and encourage EV's owners as active players in the electricity market [9][10]. Unidirectional vehicle-to-grid (V2G) technology is a mechanism that the EV load aggregators in a sizeable number can participate in energy ancillary services due to much faster ramping capability than gas turbines [11][12].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pool strategy of a producer coordinated with vehicle-to-grid services to maximize profitability

Tavakoli

Negnevitsky

Muttaqi

2015

2015 Australasian Universities Power Engineering Conference (AUPEC)

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Abstract-This paper investigates the impact of coordinating vehicle-to-grid (V2G) services with a producer on the price amounts and the market outcomes. A stochastic intra-hour bilevel model is developed for an electricity pool including the day-ahead and real-time markets. The conditional value at risk (CVaR) function takes into account to control high trading risks which are arisen from uncertainties due to high wind penetration and EVs. The problem is formulated from a mathematical program with equilibrium constraints (MPEC) to a mixed-integer linear program (MILP). The simulation results demonstrate the benefits of coordinating V2G services with a strategic producer for the increasing profitability, social welfare and optimizing EV charging profiles.

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Section: Market Framworkmentioning

confidence: 99%

Section: (9)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Pool strategy of a producer coordinated with vehicle-to-grid services to maximize profitability

Tavakoli

Negnevitsky

Muttaqi

2015

2015 Australasian Universities Power Engineering Conference (AUPEC)

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“…Frequency regulation has been considered in [10], where an optimal centralized control strategy was proposed. In [11], the authors studied the unidirectional V2G and developed an optimal algorithm for unidirectional regulation. In [12], Sortomme et al proposed an optimal energy and ancillary service scheduling strategy that maximizes profits to the aggregator.…”

Section: Related Workmentioning

confidence: 99%

A contract-based approach for ancillary services in V2G networks: Optimality and learning

Gao

Chen

Wang

et al. 2013

2013 Proceedings IEEE INFOCOM

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Abstract-With the foreseeable large scale deployment of electric vehicles (EVs) and the development of vehicle-to-grid (V2G) technologies, it is possible to provide ancillary services to the power grid in a cost efficient way, i.e., through the bidirectional power flow of EVs. A key issue in such kind of schemes is how to stimulate a large number of EVs to act coordinately to achieve the service request. This is challenging since EVs are self-interested and generally have different preferences toward charging and discharging based on their own constraints. In this paper, we propose a contract-based mechanism to tackle this challenge. Through the design of an optimal contract, the aggregator can provide incentives for EVs to participate in ancillary services to power grid, match the aggregated energy rate with the service request and maximize its own profits. We prove that under mild conditions, the optimal contract-based mechanism takes a very simple form, i.e., the aggregator only needs to publish an optimal unit price to EVs, which is determined based on the statistical distribution of EVs' preferences. We then consider a more practical scenario where the aggregator has no prior knowledge regarding the statistical distribution and study how should the aggregator learn the optimal unit price from its interactions with EVs. Simulation results are shown to verify the effectiveness of the proposed contract-based mechanism.

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“…The charging demand of numerical EVs leads to the challenge for the operation of micro-grids. Optimal operation of an aggregator for controlled EV charging has been studied in [11][12][13]. In [11], an aggregator that made efficient use of the distributed power of EVs was proposed to produce the desired grid-scale power.…”

Section: Introductionmentioning

confidence: 99%

Modelling the benefits of smart energy scheduling in micro-grids

Cai

Huang

Xie

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

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Abstract--This paper presents a smart energy management strategy (SMES) to optimise the economic operation in the microgrid. As a special and important component of smart grids, the micro-grid acts as a bridge to bundle renewable generators, energy storage systems (ESSs) and electric vehicles (EVs) together. It can be operated either by connecting to upstream distribution systems or isolated with the help of ESSs. Economic model of the micro-grid is established considering the influence of energy prices in the day-ahead market. SMES is utilised to schedule the power supply/demand of diversified sources to obtain the optimal economic operation. Smart management of ESSs, EVs and power exchange with the upstream grid if possible are simplified into a single-objective optimisation in the SEMS. Serial quadratic programming (SQP) is employed to achieve a practical method for energy management based on three different operation policies and produces diagrams of the obtained results.Index Terms--Micro-grid, economic model, day-ahead energy market, smart energy management strategy (SEMS), serial quadratic programming (SQP).

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Optimal Charging Strategies for Unidirectional Vehicle-to-Grid

Cited by 648 publications

References 16 publications

Pool strategy of a producer coordinated with vehicle-to-grid services to maximize profitability

Pool strategy of a producer coordinated with vehicle-to-grid services to maximize profitability

A contract-based approach for ancillary services in V2G networks: Optimality and learning

Modelling the benefits of smart energy scheduling in micro-grids

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