A Decentralized Bilateral Energy Trading System for Peer-to-Peer Electricity Markets

• Published in: IEEE transactions on industrial electronics (1982) Vol. 67; no. 6; pp. 4646 - 4657
• Main Authors: Khorasany, Mohsen, Mishra, Yateendra, Ledwich, Gerard
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-06-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bilateral trading; Computer simulation; Constraint modelling; Convergence; Convex functions; Data exchange; decartelized market; Distributed generation; Electricity; Electricity consumption; Electricity supply industry; Energy; Energy sources; Gradient methods; market framework design; Peer to peer computing; peer-to-peer (P2P); Players; Power marketers; Product differentiation; Redesign; Resource management; Supply & demand
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2931229

Increase in the deployment of distributed energy resources (DERs) has triggered a new trend to redesign electricity markets as consumer-centric markets relying on peer-to-peer (P2P) approaches. In the P2P markets, players can directly negotiate under bilateral energy trading to match demand and supply. The trading scheme should be designed adequately to incentivise players to participate in the trading process actively. This article proposes a decentralized P2P energy trading scheme for electricity markets with high penetration of DERs. A novel algorithm using primal-dual gradient method is described to clear the market in a fully decentralized manner without interaction of any central entity. Also, to incorporate technical constraints in the energy trading, line flow constraints are modeled in the bilateral energy trading to avoid overloaded or congested lines in the system. This market structure respects market players' preferences by allowing bilateral energy trading with product differentiation. The performance of the proposed method is evaluated using simulation studies, and it is found that market players can trade energy to maximize their welfare without violating line flow constraints. Also, compared with other similar methods for P2P trading, the proposed approach needs lower data exchange and has a faster convergence.