Industrial hydrogen demand response for adaptive robust operation of electric hydrogen integrated energy systems

The electric hydrogen integrated energy system (EHIES) enables coordinated multi-energy management and offers significant decarbonization benefits, making it a promising energy management paradigm for sectors including manufacturing and transportation. This study examines the operational characteristics of EHIES and proposes a two-layer optimization framework tailored to the hydrogen consumption process requirements of industrial applications. An industrial demand response (DR) model is formulated through an analysis of the temporal coupling among heterogeneous energy-consuming equipment across workshops within the hydrogen industry value chain. Based on industrial hydrogen utilization processes, corresponding DR rules are then defined. To address the forecast errors in wind and solar power output during the day-ahead operation phase of the EHIES, a robust optimization (RO) approach is adopted to construct an uncertainty optimization model. To mitigate the conservativeness of the conventional RO, a new adaptive RO (NARO) method is introduced, enabling decision-makers to balance conservatism and risk more effectively. Additionally, an intra-day rolling operation model is established to validate the effectiveness of the day-ahead scheduling decisions. Case study simulations verify the economic efficiency, low-carbon performance, and operational effectiveness of the proposed industrial DR model and NARO method.