Robust capacity optimization and low-carbon retrofit of integrated energy systems considering multi-timescale uncertainties and hydrogen integration

Hydrogen technologies have attracted increasing attention in the realm of renewable energy integration and decarbonization. This paper investigates the optimal configuration and low-carbon retrofit of a regional integrated energy system (IES) considering the integration of renewable energy sources (RES) and hydrogen energy. Hydrogen is explicitly modeled as a multi-energy coupling carrier, enabling coordinated interactions among power, gas, and heat networks through hybrid hydrogen production, cascade storage, and heat recovery. To this end, a planning and intertemporal operational optimization model is proposed to account for economic viability, carbon emissions, and system performance, while coordinating multi-timescale energy storage devices in the hydrogen-based IES (HB-IES). To address the challenges posed by source–load uncertainties across multiple timescales, we propose an improved representative-week selection method based on agglomerative hierarchical clustering (AHC) to capture long-term variability and support effective seasonal-storage operation modeling. In parallel, a robust optimization framework is employed to enhance the model’s sensitivity to short-term intermittency. The column-and-constraint generation (C&CG) algorithm is adopted to efficiently obtain globally optimal solutions to the resulting bi-level optimization problem. Numerical experiments verify the effectiveness of the proposed planning framework, demonstrating at least a 13.25% reduction in carbon emissions and a 3.5% decrease in lifecycle cost compared with an IES model that considers only electricity-hydrogen coupling. Sensitivity analyses further reveal interactions among carbon emissions, RES capacity, cost efficiency, and internal energy share, offering practical insights for designing low-carbon and resilient IESs.