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Transforming Energy Networks via Peer-to-Peer Energy Trading: The Potential of Game-Theoretic Approaches

Author(s): Tushar, Wayes; Yuen, Chau; Mohsenian-Rad, Hamed; Saha, Tapan; Poor, H Vincent; et al

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Abstract: Peer-to-peer (P2P) energy trading has emerged as a next-generation energy-management mechanism for the smart grid that enables each prosumer (i.e., an energy consumer who also produces electricity) of the network to participate in energy trading with other prosumers and the grid. This poses a significant challenge in terms of modeling the decisionmaking process of the participants' conflicting interests and motivating prosumers to participate in energy trading and cooperate, if necessary, in achieving different energy-management goals. Therefore, such a decisionmaking process needs to be built on solid mathematical and signal processing principles that can ensure an efficient operation of the electric power grid. This article provides an overview of the use of game-theoretic approaches for P2P energy trading as a feasible and effective means of energy management. Various game- and auction-theoretic approaches are discussed by following a systematic classification to provide information on the importance of game theory for smart energy research. This article also focuses on the key features of P2P energy trading and gives an introduction to an existing P2P testbed. Furthermore, the article gives specific game- and auction-theoretic models that have recently been used in P2P energy trading and discusses important findings arising from these approaches.
Publication Date: 27-Jun-2018
Citation: Tushar, Wayes, Yuen, Chau, Mohsenian-Rad, Hamed, Saha, Tapan, Poor, H Vincent, Wood, Kristin L. (2018). Transforming Energy Networks via Peer-to-Peer Energy Trading: The Potential of Game-Theoretic Approaches. IEEE Signal Processing Magazine, 35 (4), 90 - 111. doi:10.1109/msp.2018.2818327
DOI: doi:10.1109/msp.2018.2818327
ISSN: 1053-5888
EISSN: 1558-0792
Pages: 90 - 111
Type of Material: Journal Article
Journal/Proceeding Title: IEEE Signal Processing Magazine
Version: Author's manuscript

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