Optimizing Load Dispatch in Iron and Steel Enterprises Aligns with Solar Power Generation and Achieves Low-Carbon Goals

This study develops an optimization-based scheduling framework for coordinating the energy-intensive operations of a steel enterprise with estimated solar power availability. Unlike prior approaches that focus primarily on process efficiency or carbon reduction in isolation, the proposed model integrates demand response with linear programming to improve solar utilization while respecting load priorities. The solar generation profile is derived from typical meteorological year (TMY) irradiance data, adjusted for panel efficiency and system parameters, thereby serving as an estimated input rather than measured data. Simulation results over a 31-day horizon show that coordinated scheduling can reduce grid dependence and increase solar energy utilization by up to 99% under the simulated conditions. While the findings demonstrate the potential of load scheduling for industrial decarbonization, they are based on estimated solar data and a simplified system representation. Future work should incorporate real-world solar measurements and stochastic models to address uncertainty and further validate industrial applicability.