Open Access

ARTICLE

Optimized Scheduling of an Integrated Electro-Gas Energy System with Hydrogen Storage Utilizing Information Gap Decision Theory

Xu Liu^*, Hongsheng Su

School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China

* Corresponding Author: Xu Liu. Email:

(This article belongs to the Special Issue: Integration of Hybrid Renewable Energy Systems for Sustainable Development)

Energy Engineering 2026, 123(4), 16 https://doi.org/10.32604/ee.2025.072246

Received 22 August 2025; Accepted 17 October 2025; Issue published 27 March 2026

Abstract

Further investigation is warranted into the collaborative function of carbon capture and electrolysis-to-gas conversion technologies within integrated electro-gas energy systems, as well as optimized scheduling that addresses the variability of wind and solar energy, to promote multi-energy complementarity and energy decarbonization while enhancing the capacity to absorb new energy. This work presents an optimized scheduling model for electro-gas integrated energy systems that include hydrogen storage, utilizing information gap decision theory (IGDT). A model is constructed that integrates the synergistic functions of carbon capture and storage (CCS), power-to-gas (P2G), and gas turbine units through electrical coupling. A carbon ladder trading mechanism is implemented to mitigate carbon emissions inside the system. A day-ahead optimization scheduling model is subsequently built to maximize system operational profit and ensure hydrogen storage safety, while considering economic viability, low-carbon performance, and safety. Secondly, the trinitrotoluene (TNT) equivalent approach and the half-lethal range were employed to quantify the safety concerns associated with hydrogen storage tanks, offering the model optimization guidance and conservative management. Ultimately, the CCS-P2G integrated operation accounted for the unpredictability in wind and solar energy production through the application of information gap decision theory. The model was solved using the GUROBI solver. The findings indicate that the proposed approach diminishes system carbon emissions by 66%, attains complete integration of wind and solar energy, and eliminates hazardous working time for hydrogen storage tanks, reducing it from 10 h to zero. It ensures system safety while guaranteeing profits of at least 90% of the anticipated value, accounting for changes in wind and solar output within ±14%. This confirms the model’s efficacy in improving renewable energy integration rates, facilitating low-carbon, cost-effective, and secure system operation, while mitigating the unpredictability of renewable energy production.

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Keywords

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