Distributed Dispatch of Multi-Community Integrated Energy Systems Over Nonideal Communication Networks

This paper develops a privacy-preserving distributed optimization framework for multi-community integrated energy systems (MCIES), specifically addressing the overlooked challenge of energy-carbon coordination under nonideal communication environments. Current research predominantly assumes ideal communication networks, neglecting practical constraints like packet loss and channel noise. To bridge this gap, an energy-carbon coordination optimization model for MCIES is formulated firstly. Then, a novel distributed optimization method based on the relaxed alternating direction method of multiplier (RADMM) is introduced, achieving global optimality through localized neighbor communication. Moreover, different robust RADMM-based approaches are proposed to enable the distributed coordinated optimization model of MCIES to function under nonideal communication conditions, encompassing lossy and noisy communications. Finally, the case study demonstrates the robust RADMM exhibits faster convergence and higher robustness under the nonideal communication conditions.