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

TLDR

The rise of distributed energy resources has spurred a shift toward consumer‑centric peer‑to‑peer electricity markets where participants negotiate bilateral trades. This article proposes a decentralized P2P energy trading scheme designed for markets with high DER penetration. The scheme employs a primal‑dual gradient algorithm to clear the market in a fully decentralized manner, incorporates line‑flow constraints, and allows product‑differentiated bilateral trades that respect players’ preferences. Simulation results demonstrate that participants can maximize welfare while obeying line‑flow limits, and the method achieves lower data exchange and faster convergence than comparable P2P approaches.

Abstract

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.