Optimal scheduling of integrated electricity-heat-storage systems for green industrial heating

This study presents an optimal scheduling approach for an integrated electricity-heat-storage energy system to enhance renewable energy utilization in industrial heating applications. Addressing the challenges of renewable power intermittency and the limitations of traditional power-to-heat conversion in supplying multi-level steam, we develop a mixed-integer programming model that coordinates wind turbines, grid electricity, electrode boilers, and hierarchical solid-state thermal storage. Using representative daily wind power and load profiles as inputs, the system is optimized with Gurobi to ensure stable supply of electrical and multi-pressure steam loads while minimizing total operating cost and carbon emissions. Simulation results demonstrate that the proposed strategy significantly increases renewable energy absorption, enables efficient cascade use of thermal energy, and reduces fluctuations in both power and steam supply. The flexible interactions between wind power generation and thermal storage boilers allow excess wind energy to be absorbed during off-peak periods and released during demand peaks. The methodology offers an effective solution for improving renew able energy integration, operational reliability, and flexibility in industrial heating systems, providing a valuable reference for large-scale green power applications and supporting the decarbonization of energy-intensive industries.