System-Level Techno-Economic Optimization of Decarbonized Industrial Thermal Energy Systems via Active Load Restructuring
Abstract
In cold-region industrial parks, prolonged heating seasons and intensive hot water demands trigger severe temporal mismatches between stochastic renewable generation and rigid thermal requirements. To address this, a multidimensional synergistic optimization framework for industrial thermal energy systems is proposed. The physical architecture integrates wind, solar, and shallow geothermal energy with hybrid storage, establishing thermodynamic boundaries. Concurrently, a customized solver is developed for the coupled electro-thermal scheduling problem. At its core, the active load restructuring strategy (ALRS) exploits the thermal inertia of thermal storage tanks and leverages the high coefficient of performance of ground source heat pumps. ALRS restructures the all-day hot water supply load to nighttime windows characterized by abundant wind power and off-peak tariffs, achieving profound source–load temporal decoupling and transforming rigid thermal demands into cross-period virtual flexible assets. Assessments demonstrate that the proposed strategy reduces typical-day electricity costs by 82.51%. Compared to a grid-dependent rigid baseline, comprehensive daily operational and carbon emission costs decrease by 71.9% and 90.2%, respectively. This study demonstrates the potential of translating thermal flexibility into coordinated energy management and provides a system-level reference for the low-carbon operation of industrial thermal energy systems.