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

Na Sun, Hongxu He and Haiying Dong ()
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Na Sun: School of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Hongxu He: School of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Haiying Dong: School of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Energies, 2025, vol. 18, issue 22, 1-22

Abstract: 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.

Keywords: integrated energy system; information gap decision theory; fuzzy chance-constrained programming; electric-hydrogen hybrid energy storage; carbon trading; optimal dispatch (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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