4.7 Article

Burdening proportion and new energy-saving technologies analysis and optimization for iron and steel production system

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 172, Issue -, Pages 2153-2166

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.11.204

Keywords

Iron and steel production system; Optimization model; Energy consumption and CO2 emission minimization; Burdening proportion analysis and optimization; New energy-saving technology

Funding

  1. National Key Basic Research and Development Program of China (973) [2012CB720405]
  2. National Nature Science Foundation of Naval University of Engineering [HG DYDJJ-13002]

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Taking the 1780 mm hot rolling strip production process as an example, an optimization model covering the sinter matching process to the steel rolling product output for iron and steel production system (ISPS) is established. Linear programming (LP) and nonlinear programming (NLP) methods and e-p analysis are applied. Energy consumption and CO2 emission minimizations are taken as optimization objectives. Total 61 key constraints are considered. The optimal scenario of burdening proportions and operation parameters of blast furnace are obtained. After optimization, the comparable energy consumption per ton steel of ISPS decreases by 2.39% and the comprehensive one by 2.29% compared with the initial values, respectively. Moreover, on specific procedures and process levels, applications of new energy saving technologies will have significant effects on system energy consumption. When these new energy-saving technologies are synthesizing adopted as the following combination: hierarchical porous sintering, equivalent calorific value injection + sensible heat recovery of high temperature slags in blast furnace and converter + sensible heat recovery of high temperature converter gas(without considering the oxygen blast furnace), the maximum energy conservation of 20.63 kgce per ton steel can be achieved, which can make the system energy consumption approximately decrease by 3.40%. When the combination above is applied to the proposed optimization model, the energy-saving effect can attain 5.69%. (C) 2017 Elsevier Ltd. All rights reserved.

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