Thermophysical Model for Online Optimization and Control of the Electric Arc Furnace

A dynamic, first-principles process model for a steelmaking electric arc furnace has been developed. The is an integrated part of application designed optimization during operation the furnace. Special care taken to ensure that non-linear robust and accurate enough real-time optimization. formulated in terms state variables ordinary differential equations adapted data using recursive parameter estimation. Compared other models available literature, focus this integrate auxiliary order best predict energy efficiency heat transfer limitations Model predictions are reasonable agreement with steel temperature weight measurements. Simulations indicate industrial deployment Predictive Control applications derived from can result electrical consumption savings 1–2%.