A Game-Theoretic Approach to Energy Trading in the Smart Grid

By Yunpeng Wang, Walid Saad, Zhu Han, H. Vincent Poor, Tamer Basar. IEEE Transactions on Smart Grid, 2013

398 citations recorded by the source corpus.

Electric storage units constitute a key element in the emerging smart grid system. In this paper, the interactions and energy trading decisions of a number of geographically distributed storage units are studied using a novel framework based on game theory. In particular, a noncooperative game is formulated between storage units, such as plug-in hybrid electric vehicles, or an array of batteries that are trading their stored energy. Here, each storage unit's owner can decide on the maximum amount of energy to sell in a local market so as to maximize a utility that reflects the tradeoff between the revenues from energy trading and the accompanying costs. Then in this energy exchange market between the storage units and the smart grid elements, the price at which energy is traded is determined via an auction mechanism. The game is shown to admit at least one Nash equilibrium and a novel algorithm that is guaranteed to reach such an equilibrium point is proposed. Simulation results show that the proposed approach yields significant performance improvements, in terms of the average utility per storage unit, reaching up to 130.2% compared to a conventional greedy approach.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/a7773661b9b524ca3fbb0788cb224742f7c5a0cb

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Citations in the corpus

Peer-to-Peer Energy Trading in a Prosumer-Based Community Microgrid: A Game-Theoretic Model (2019, background): “NE exists in the game if the following conditions are satisfied [27].”
Distributed Energy Trading: The Multiple-Microgrid Case (2013, background): “[22] consider a scenario where a set of geographi-”
Bilateral Contract Networks for Peer-to-Peer Energy Trading (2019, background): “The designs in [18], [19] consider isolated systems, with a single market allowing all generators and consumers to trade with one another.”
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches (2018, methodology): “[1], [3], [11], [14], [18], [21], [25], [29], [35], [40], [41] [23], [24], [36]”