Optimized Scheduling of Integrated Energy Systems Based on Carbon Flow Theory and Master-Slave Game Models

With growing global attention to climate change and sustainable development, improving energy structures and curbing carbon emissions have become essential goals for integrated energy systems (IES). Carbon reduction strategies must be addressed from both the supply and user perspectives. This study introduces an IES optimization and scheduling approach based on carbon emission flow theory and a leader-follower game model. Initially, the leader-follower game framework is established, positioning the supply side as the leader and the user side as the follower. Through a carbon trading mechanism, the supply side employs carbon emission flow principles to distribute emission quotas to the user side. Moreover, a low-carbon demand response strategy is designed from the user's standpoint to support optimal low-carbon scheduling on the supply side. The differential evolution algorithm is utilized to analyze the interaction strategies between supply and demand. Simulation findings confirm the method's economic viability and environmental benefits.