A communication-efficient coalition graph game-based framework for electricity and carbon trading in networked energy hubs

Abstract

In this paper, we study the interactions between energy hubs under a hybrid topology with an incomplete network for local electricity trading and a complete network for local carbon trading. Based on the hybrid topology, we develop a two-stage communication-efficient coalition graph game-based framework to achieve communication cost reduction and fair profit distribution for energy hubs. An electricity trading optimization problem and a carbon trading optimization problem are considered in the first and second stages, respectively. A communication-censored alternating direction method of multipliers (COCA) with a censoring strategy is applied to solve the optimization problems in a decentralized manner. The profits obtained through the hybrid topology are fairly distributed by the profit distribution schemes based on the Myerson value and Shapley value, which are designed for incomplete and complete networks, respectively. Simulation results demonstrate that the profit distribution schemes can fairly distribute the profits obtained through the local trading. Moreover, compared to the noncooperative benchmark, the proposed framework can reduce the total payment and carbon emissions of energy hubs by 22.64% and 33.45%, respectively. Compared to the alternating direction method of multipliers (ADMM), the COCA can reduce total communication cost of energy hubs by 18.99%.