Optimizing Industrial Park Power–Hydrogen–Thermal Systems for Low-Carbon Economy: Accounting for Nonlinear Polarization and Waste-Heat Utilization

To address high carbon emissions, high operational costs, and severe renewable-energy curtailment in industrial parks, this paper proposes a multi-objective optimal dispatch method for an integrated electricity–hydrogen–thermal energy system. First, load-dependent reduced-order models informed by polarization characteristics are employed to represent the nonlinear efficiency characteristics of hydrogen conversion equipment, alongside a hydrogen–thermal cascade utilization strategy that incorporates recoverable fuel-cell waste heat into the aggregate industrial thermal-energy balance. On this basis, a bi-objective optimal scheduling model aiming to minimize daily operating costs and daily operational carbon emissions is formulated and solved via an improved NSGA-II algorithm and fuzzy set theory to extract the optimal compromise scheme. In a case study of a typical chemical industrial park in Xinjiang, the proposed framework achieves 100% renewable-energy accommodation, with zero wind and solar curtailment over the studied 24 h scheduling horizon. Compared to the baseline hydrogen-free model, daily operating costs and daily operational carbon emissions drop by 81.5% and 75.3%, respectively, with a 25.23% thermal waste-heat coverage ratio achieved. Concurrently, the internal rate of return for legacy renewable assets rises from 5.8% to 8.3%. These findings provide technical decision support for the low-carbon transformation and multi-energy synergistic utilization of energy-intensive industrial sectors.