A real-time cost optimization of two-section oven system with discrete gradient extremum seeking control: An experimental study in iron and steel industry. (February 2023) - Yilmaz, Süleyman; Furat, Murat
Abstract: The heavy industry plants are focused on finding ways to minimize energy costs, which is one of the most significant costs of production. In this paper, a case study on a real oven system used in a steel strip production line is performed. Oven systems consume different types of energy simultaneously. Therefore, energy cost optimization is a good case study for the oven systems. The real oven system studied in the present study consists of two sections with eight heating zones. A natural gas burner and a recirculation fan with a power of 45 kW are installed in each zone for continuous heating of steel strips. We improved Discrete Gradient Extremum Seeking Control (DGESC) in the oven system without changing the oven structure and its built-in burner controller and optimized the fan speeds so that the total cost of the heating process is minimized. The improved DGESC was evaluated during steel strip production with the constraints related to the oven safety, measurement device characteristics, and delays for stabilization. The measure of energy consumption was obtained from the oven automated software and compared with the consumption when using the oven manufacturer's recommended settings. At the end of the production, the improved DGESC strategy showed that the same output can be produced with less cost at different operating speeds of the fans. In particular, the total cost of the electrical energy and natural gas was reduced by 3.44% when using 78% of fan speed instead of using 70% recommended by the manufacturer. The promising results of the improved DGESC can be further enhanced by upgrading the oven system for individual measurements. Highlights: A case study of Discrete Gradient Extremum Seeking Control (DGESC) is performed. DGESC is adapted to the oven system in a steel plant. Challenges facing the implementation of DGESC are overcome. A real-time energy cost optimization is performed. Sum of natural gas and electricity costs is optimized.