Energy-carbon coordination of transactive multi-community integrated energy systems under imperfect communication networks

The energy-carbon coordination within multi-community integrated energy systems (MCIES) emerges as a promising strategy for enhancing energy efficiency and mitigating carbon emissions. To safeguard the privacy of individual community integrated energy systems, distributed optimization is implemented in MCIES coordination. However, existing studies neglect the influence of imperfect communication conditions on distributed energy-carbon coordination optimization. This paper addresses this gap by presenting a distributed optimization approach for MCIES, incorporating energy sharing and carbon trading, to mitigate the impact of imperfect communication conditions. Firstly, an energy-carbon coordination optimization model for MCIES is formulated, considering the power transformer’s loading capacity to prevent congestion. Then, a novel fully distributed optimization method based on the relaxed alternating direction method of multiplier (RADMM) is proposed to solve the scheduling model of MCIES considering various imperfect communication conditions. The proposed RADMM algorithm effectively tackles convex optimization problems with coupling equality constraints over undirected networks, facilitating global optimal solutions through direct communication solely among neighboring community agents without the need for a third party. Furthermore, it enables the distributed coordinated optimization model of MCIES to function reliably even in imperfect communication environments, including lossy, noisy, and quantized communications. Simulation results demonstrate the developed scheduling model’s ability to ensure safe, economically beneficial, and environmentally friendly MCIES operation. Additionally, the proposed RADMM approach exhibits superior performance in terms of convergence rate and robustness against packet loss and corruption compared to the classical ADMM method.