A Game-Theoretic Approach to Energy Trading in the Smart Grid
Yunpeng Wang, Walid Saad, Zhu Han, H. Vincent Poor, and Tamer, Ba\c{s}ar

TL;DR
This paper models energy trading among distributed storage units in the smart grid using game theory, proposing a novel auction-based framework that improves utility outcomes significantly.
Contribution
It introduces a game-theoretic framework with an auction mechanism for energy trading among storage units, ensuring equilibrium and enhancing utility.
Findings
The game admits at least one Nash equilibrium.
The proposed algorithm guarantees convergence to equilibrium.
Simulation shows up to 130.2% utility improvement.
Abstract
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 PHEVs, 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 proposed algorithm that is…
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Taxonomy
TopicsSmart Grid Energy Management · Electric Power System Optimization · Microgrid Control and Optimization
