Chapter 4 - Integrated modeling and energetic optimization of the steelmaking process in electric arc furnaces: An industrial application

Abstract

This chapter presents an integrated modeling and optimization framework that is tailored to the optimization of the energy demand and the environmental impact of the steelmaking process in electric arc furnaces (EAF). A control vector parametrization technique is used to optimize the batch trajectories of the EAF with the goal to minimize the energy losses of the process. From these trajectories, the minimum energy demand of a batch for different operative power levels and the batch times result. This information can then be passed to scheduling algorithms that compute the optimal production schedules taking into account the cost of electric power and its CO2 footprint. A hybrid EAF process model derived from the first principles is used to predict the dynamic evolution of the EAF process. The dynamic optimization framework was used to compute optimal melting profiles for a state-of-the-art industrial ultra-high power EAF. For a series of 50 test batches, the energy consumption and the batch time of the process were reduced by 4.5% and 4.6% for one type of steel.