Economics of Electric Vehicle Charging: A Game Theoretic Approach

By Wayes Tushar, David B. Smith. IEEE Transactions on Smart Grid, 2012

376 citations recorded by the source corpus.

In this paper, the problem of grid-to-vehicle energy exchange between a smart grid and plug-in electric vehicle groups (PEVGs) is studied using a noncooperative Stackelberg game. In this game, on the one hand, the smart grid, which acts as a leader, needs to decide on its price so as to optimize its revenue while ensuring the PEVGs' participation. On the other hand, the PEVGs, which act as followers, need to decide on their charging strategies so as to optimize a tradeoff between the benefit from battery charging and the associated cost. Using variational inequalities, it is shown that the proposed game possesses a socially optimal Stackelberg equilibrium in which the grid optimizes its price while the PEVGs choose their equilibrium strategies. A distributed algorithm that enables the PEVGs and the smart grid to reach this equilibrium is proposed and assessed by extensive simulations. Further, the model is extended to a time-varying case that can incorporate and handle slowly varying environments.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8209d0f61f3d63b98e5ed42043ddc5f67afa0f3f

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Citations in the corpus

Energy Storage Sharing in Smart Grid: A Modified Auction-Based Approach (2015, neutral): “be reasonable in numerous studies such as in [11] and [38].”
Cloud Computing Applications for Smart Grid: A Survey (2015, background): “During peak hour, charging of PHEVs increases the load on smart grid [48], [49].”
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches (2018, background): “[11], [15], [18]– [22], [25]–[31] [23], [24]”
Distributed Energy Trading in Microgrids: A Game-Theoretic Model and Its Equilibrium Analysis (2015, methodology): “For examples of the applications of singleleader–multifollower Stackelberg solutions to hierarchical decision problems in a smart grid, see [42]–[44].”
A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms (2015, background): “This target is achieved by the generalized Stackelberg game presented in [222], where PHEVs select their strategies to optimize their”
Peer-to-Peer Trading in Electricity Networks: An Overview (2020, methodology): “The most popular solution concept of a non-cooperative game is the Nash equilibrium [89].”
Three-Party Energy Management With Distributed Energy Resources in Smart Grid (2014, background): “In (1), kn ln(1 + en) is the utility that the RU n achieves from consuming energy en, where kn is a preference parameter [35], [36].”