1 Department of Thermal Energy, School of Energy and Environment, Anhui University of Technology, Ma’anshan 243002, Anhui, China 2 Department of Metallurgical Engineering, School of Energy and Environment, Anhui University of Technology, Ma’anshan 243002, Auhui, China 3 Department of Construction and Environmental Engineering, School of Architectural Engineering, Anhui University of Technology, Ma’anshan 243002, Anhui, China 4 Ma’anshan Iron and Steel Co., Ltd., Ma’anshan 243003, Anhui, China
Abstract：An online model was proposed to identify the reasons behind changes in the energy consumption of the reheating furnace of a steel processing plant. The heat conversion of the furnace was analyzed and integrated with the fuel consumption of the furnace to obtain a model of the energy consumption. Combined with the mechanism analysis, the basic parameters affecting energy consumption were determined, and four key influencing factors were obtained: furnace output, furnace charging temperature, furnace tapping temperature, and steel type. The specific calculation method of the contribution of each influencing factor was derived to define the conditions of the baseline energy consumption, while the online data were used to calculate the energy value and the actual performance value of the baseline energy consumption. The contribution of each influencing factor was determined through normalization. The cloud platform was used for database reconstruction and programming to realize the online intelligent evaluation of the energy consumption of the reheating furnace. Finally, a case study of the evaluation of the practical energy consumption of a steel rolling furnace in a steel plant was presented. The intelligent evaluation results were quantified and displayed online, and the performance of the system in reducing production line energy consumption was demonstrated.
Xiang-jun Bao,Jing Xu,Guang Chen, et al. Mechanism and application of an online intelligent evaluation model for energy consumption of a reheating furnace[J]. Journal of Iron and Steel Research International, 2023, 30(1): 102-111.
2023, Vol. 30 
