A Two-Stage Optimal Dispatch Strategy for Electric-Thermal-Hydrogen Integrated Energy System Based on IGDT and Fuzzy Chance-Constrained Programming

To address the economic and reliability challenges of high-penetration renewable energy integration in electricity-heat-hydrogen integrated energy systems and support the dual-carbon strategy, this paper proposes an optimal dispatch method integrating Information Gap Decision Theory (IGDT) and Fuzzy Chance-Constrained Programming (FCCP). An IES model coupling multiple energy components was constructed to exploit multi-energy complementarity. A stepped carbon trading mechanism was introduced to quantify emission costs. For interval uncertainties in renewable generation, IGDT-based robust and opportunistic dispatch models were established; for fuzzy load uncertainties, FCCP transformed them into deterministic equivalents, forming a dual-layer “IGDT-FCCP” uncertainty handling framework. Simulation using CPLEX demonstrated that the proposed model dynamically adjusts uncertainty tolerance and confidence levels, effectively balancing economy, robustness, and low-carbon performance under complex uncertainties: reducing total costs by 12.7%, cutting carbon emissions by 28.1%, and lowering renewable curtailment to 1.8%. This study provides an advanced decision-making paradigm for low-carbon resilient IES.