Conference article

Energy System Optimization for a Scrap Based Steel Plant Using Mixed Integer Linear Programming

Johan Riesbeck
Centre for Process Integration in Steelmaking, Swerea MEFOS, Luleå, Sweden

Philip Lingebrant
Höganäs AB, Höganäs, Sweden

Erik Sandberg
Centre for Process Integration in Steelmaking, Swerea MEFOS, Luleå, Sweden

Chuan Wang
Centre for Process Integration in Steelmaking, Swerea MEFOS, Luleå, Sweden

Download articlehttp://dx.doi.org/10.3384/ecp110571676

Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:26, p. 1676-1683

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Published: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

In this work a mathematic model to simulate and optimize the energy system of a scrap based plant has been developed. Scrap based steelmaking is an energy intense production system. The potential for energy saving by system optimization is therefore high; even if the percentage of saved energy is relatively small. The model includes scrap pre-treatment; electrical arc furnace; ladle furnace and continuous casting units. To estimate the chemical compositions of the scrap charged into the EAF a statistical model based on an existing EAF plant has been used to provide the inputs to the model. Distribution factors have been used to describe the distribution of elements and oxides between the steel; slag and off gas/dust. To calculate the energy consumption in the electrical arc furnace a combination of an empirical and theoretical energy formula has been used. The model represents a general description of the most common process in electric steelmaking. It is suited to be adapted for specific plants with adjustments to the model parameters. The model gives reasonable results which follow the chemical composition of steel and slag and yield. The model can be a powerful tool to optimize the scrap mix and injectants towards energy and costs.

Keywords

Energy systems; optimization; steelmaking; EAF; MILP; linear programming

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