Optimization Scheduling of Hydrogen-Integrated Energy Systems Considering Multi-Timescale Carbon Trading Mechanisms

Amidst the escalating global challenges presented by climate change, carbon trading mechanisms have become critical tools for driving reductions in carbon emissions and optimizing energy systems. However, existing carbon trading models, constrained by fixed settlement cycles, face difficulties in addressing the scheduling needs of energy systems that operate across multiple time scales. To address this challenge, this paper proposes an optimal scheduling methodology for hydrogen-encompassing integrated energy systems that incorporates a multi-time-scale carbon trading mechanism. The proposed approach dynamically optimizes the scheduling and conversion of hydrogen energy, electricity, thermal energy, and other energy forms by flexibly adjusting the carbon trading cycle. It accounts for fluctuations in energy demand and carbon emissions occurring both before and during the operational day. In the day-ahead scheduling phase, a tiered carbon transaction cost model is employed to optimize the initial scheduling framework. During the day scheduling phase, real-time data are utilized to dynamically adjust carbon quotas and emission ranges, further refining the system’s operational strategy. Through the analysis of typical case studies, this method demonstrates significant benefits in reducing carbon emission costs, enhancing energy efficiency, and improving system flexibility.