Distributed Energy Management of Electricity-Heat-Hydrogen Integrated Energy System Based on Neurodynamics

Due to the increasingly prominent multi-agent, large-scale and decentralized characteristics of the integrated energy system (IES), the traditional centralized optimization method that needs a global processor is no longer applicable. This paper adopts a distributed optimization method based on neurodynamics to address the energy management of the electricity-heat-hydrogen IES. The optimization results can converge within a limited number of iterations times. In addition, the validity and superiority of the method are verified through comparative analyses with results obtained from both centralized optimization methods and the alternating direction method of multipliers (ADMM). In response to the malicious eavesdropping behavior that may exist in the process of information interaction among agents in the system, a protocol incorporating noise item and secret function for information exchange is devised to provide effective privacy protection for transmitted data. Case studies based on a testing system are carried out and the simulation results demonstrate the effectiveness of the method.