Two-Stage Community Energy Trading Under End-Edge-Cloud Orchestration

Abstract

The end-edge-cloud orchestration of the virtual power plant (VPP) enables the edge server to timely serve community users. By deploying the community energy storage system (CESS) and the community peer-to-peer (P2P) market, prosumers can form energy communities to achieve self-sufficiency of energy and independence from fuel-based power generators. This article proposed a two-stage community energy trading model under end-edge-cloud orchestration. The community P2P trading is the first stage where the edge server can execute the automatic bidding process for multiple buyers and sellers based on the real-time users’ energy profiles and the Bayesian-game-based pricing mechanism. The trading between the retailer and energy communities is the second stage where the edge server can dynamically update the optimal operation of the CESS based on the dynamic pricing mechanism. An original centralized optimization problem is decomposed into subproblems for each stakeholder and solved through the alternating direction method of multipliers (ADMM). Considering ADMM needs multiple information exchanges, a general form of the communication-censored ADMM for sharing problems is proposed to decrease the communication cost. Numerical simulations prove that the proposed mechanism can effectively increase transaction efficiency, avoid the new demand peak brought by the utilization of the CESS, and decrease the communication cost.