Distributed Online Generalized Nash Equilibrium Tracking for Prosumer Energy Trading Games

TL;DR

This paper develops a distributed online algorithm for prosumer energy trading modeled as a generalized Nash game, ensuring convergence and effectiveness in dynamic environments with validation on microgrid simulations.

Contribution

It introduces a novel distributed online algorithm for GNE tracking in prosumer energy markets, with proven convergence and bounded regret in time-varying settings.

Findings

Proved existence and uniqueness of GNE in prosumer trading.

Demonstrated the algorithm's bounded regret over time.

Validated performance through microgrid simulations.

Abstract

With the proliferation of distributed generations, traditional passive consumers in distribution networks are evolving into "prosumers", which can both produce and consume energy. Energy trading with the main grid or between prosumers is inevitable if the energy surplus and shortage exist. To this end, this paper investigates the peer-to-peer (P2P) energy trading market, which is formulated as a generalized Nash game. We first prove the existence and uniqueness of the generalized Nash equilibrium (GNE). Then, an distributed online algorithm is proposed to track the GNE in the time-varying environment. Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice. Finally, numerical results with six microgrids validate the performance of the algorithm.