Peer-to-Peer Multi-Energy Trading Among Heterogeneous Building Prosumers via Asynchronous Distributed Algorithm

Xiaolong Jin, Xiaoyu Wang, Hongjie Jia, Yunfei Mu, Qiuwei Wu, Wei Wei

Abstract: Smart buildings in the integrated community energy system (ICES) are normally equipped with distributed energy resources (DERs), thereby creating building prosumers with both energy production and consumption. Peer-to-peer (P2P) energy trading among building prosumers can bring higher economic benefits for them. Therefore, a P2P multi-energy trading scheme among building prosumers is proposed, which fully explores the flexibility of buildings’ heating loads based on the thermal dynamics of buildings with different thermal insulation properties. Each building prosumer is heterogeneous in terms of its computation and communication infrastructures. This results in a heavy computation burden with the traditional centralized method. To improve the computational efficiency for P2P trading among heterogeneous building prosumers, an asynchronous distributed algorithm based on alternating direction method of multipliers (ADMM) is developed to enable each prosumer to trade energy asynchronously instead of waiting for the trading information from others with poor infrastructure. This asynchronous procedure integrated with the prediction and anomaly detection steps can further accelerate the convergence speed of P2P trading. Simulation results verify the effectiveness of the proposed trading scheme and the feasibility and solution optimality of the proposed algorithm.