A Decentralized Peer-to-Peer Energy Trading Model in Integrated Electric-Thermal System

To promote the energy accommodation of both electrical and heating power while considering the source-load uncertainties, this paper proposes a peer-to-peer (P2P) energy trading model among prosumers in the integrated electric-thermal system, considering the energy trading agent (ETA) with self-build energy system. The Solar Heat-Pump Hybrid Thermal Water System (SPTS) and the transferring loss of heating power is considered and modelled based on the principle of steady-state thermal transfer. Since the variations of load and PV cannot be described by any single common distribution, the chance-constraints programming based on the Gaussian mixture model (GMM) is proposed to handle the uncertainty of the net load. As the proposed power trading problem is a non-convex problem with binary variables, an improved distributed alternating direction method of multiplier (ADMM) based on the predictor-corrector and two-stage cycle iterations is proposed to enhance the convergence performance of standard ADMM. Finally, an example simulation verifies the effectiveness, results show that the proposed model can decrease the total cost by 26.7% and enhance local energy balance by 61.8% compared to other cases.