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

Metals

Stein O. Wasbø¹  Sudi Jawahery¹  Andreas Hammervold¹  Ville-Valtteri Visuri²  Niko Hyttinen²  Martin Schlautmann³ 

[1] Cybernetica AS, Leirfossvegen 27, 7038 Trondheim, Norway;Research and Development, Outokumpu Stainless Oy, Terästie, 95490 Tornio, Finland;VDEh-Betriebsforschungsinstitut GmbH, Sohnstraße 69, 40237 Düsseldorf, Germany;

关键词: electric arc furnace;    mathematical modeling;    model predictive control;   

DOI  :  10.3390/met11101587

来源: DOAJ

【 摘 要 】

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

【 授权许可】

Unknown