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›› 2017, Vol. 17 ›› Issue (1): 178-182.DOI: 10.12034/j.issn.1009-606X.216267

• 过程与工艺 • 上一篇    下一篇

高炉多目标优化模型的建立及验证

车晓锐,张宗旺,张宏博   

  1. 北京科技大学冶金与生态工程学院
  • 收稿日期:2016-08-09 修回日期:2016-09-02 出版日期:2017-02-20 发布日期:2017-02-22
  • 通讯作者: 车晓锐

Establishment and Validation of Multi-objective Optimization Model of Blast Furnace

CHE Xiao-rui 1,ZHANG Zong-wang 2,ZHANG Hong-bo 2   

  1. 1. School of Metallurgical and Ecological Engineering, Beijing University of Science and Technology
    2. Institute of Metallurgical and Ecological Engineering, Beijing University of Science and Technology
  • Received:2016-08-09 Revised:2016-09-02 Online:2017-02-20 Published:2017-02-22
  • Contact: CHE Xiao-rui

摘要: 采用线性规划方法,建立了以能耗和成本为目标函数的高炉炼铁优化数学模型,根据目标函数和高炉过程特性确定优化变量和约束条件,利用Lingo软件设计程序求得优化结果,通过单目标优化得到多目标最优化模型,利用该优化模型并借助Origin软件分析了焦比、鼓风温度、焦炉煤气的喷吹量等因素对能耗和成本的影响,提出节能降耗的途径,并与生产数据比较验证模型的可靠性. 结果表明,与高炉生产数据相比,按标准煤计,模型优化后能耗降低了24.1 kg/t,成本节省了42.7 ¥/t. 高炉降低能耗和节约成本的措施为:降低焦比,提高喷煤比,增加焦炉煤气喷吹量,富氧及提高热风温度.

关键词: 高炉, 能耗, 成本, 线性规划, 多目标最优化

Abstract: Blast furnace iron-making optimization model is based on material balance and heat balance of the iron-making process. An optimized mathematical mode, whose objective function were the energy consumption and cost, is established using the method of linear programming. Optimization variables and constraints were determined according to the objective function and the characteristics of the blast furnace process. The optimized results were obtained by designing programs with Lingo software, and the multi-objective optimization was obtained by single objective optimization. The superiority of the model was verified by comparing the calculated data with the actual production data. The optimization model, together with the Origin software, was used to analyze the impact of factors such as the coke rate, blast temperature, injection quantity of coke oven gas on energy consumption and cost. At the meantime, some methods to reduce energy consumption were introduced. The results showed that model is optimized to reduce energy consumption by 24.1 kg/t and cost saved selections 42.7 ¥/t compared with the blast furnace production data, according to the standard coal gauge. Hence, there are several measures to reduce energy consumption and cost savings for the blast furnace: to reduce coke rate, improve the coal injection ratio, increase the amount of coke oven gas injection, enrich the oxygen and improve hot blast temperature.

Key words: blast furnace, energy consumption, cost, linear programming, multi-object optimization

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