CIESC Journal ›› 2016, Vol. 67 ›› Issue (3): 1040-1047.doi: 10.11949/j.issn.0438-1157.20151928

Previous Articles     Next Articles

Multi-objective optimization model for blast furnace production and ingredients based on NSGA-Ⅱ algorithm

HUA Changchun1, WANG Yajie1, LI Junpeng1, TANG Yinggan1, LU Zhigang1, Guan Xinping1,2   

  1. 1. School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China;
    2. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2015-12-21 Revised:2016-01-05 Online:2016-03-05 Published:2016-01-12
  • Contact: 67 E-mail:cch@ysu.edu.cn
  • Supported by:

    supported by the National Natural Science Foundation of China (61322303, 61290322).

Abstract:

Primary steelmaking is one of the most energy intensive industrial processes in the world and many researches have been done to reduce production cost and CO2 emissions of blast furnace. This paper formulates the above task as a multi-objective optimization problem, the main purpose is to optimize the production cost and CO2 emissions in the process of blast furnace production and ingredients based on the nondominated sorting-based multi-objective genetic algorithm Ⅱ (NSGA-Ⅱ). It is important to find the Pareto-optimal frontier (PF) and Pareto-optimal solutions (PS) for the multi-objective optimization problem of blast furnace, because different state of operator can be selected in PS to largely reduce the emissions and still keep the steelmaking economically feasible. Furthermore, simulation results verify the effectiveness of the proposed method for the multi-objective optimization model in the process of blast furnace production and ingredients. After optimization, the cost was reduced by about 144 CNY, and CO2 emissions were reduced by 67 kg.

Key words: blast furnace production and ingredients, NSGA-Ⅱ algorithm, cost, CO2 emissions, multi-objective optimization, Pareto-optimal solutions

CLC Number: 

  • TF4

[1] LARSSON M, DAHL J. Development of a method for analyzing energy, environmental and economic efficiency for an integrated steel plant[J]. Applied Thermal Engineering, 2006, 26 (13): 1353-1361.
[2] HELLE H, HELLE M, SAXEN H. Nonlinear optimization of steel production using traditional and novel blast furnace operation strategies[J]. Chemical Engineering Science, 2011, 66 (24): 6470-6481.
[3] SUOPAJARVI H, PONGRACZ E, FABRITIUS T. Bioreducer use in finish blast furnace iron making analysis of CO2 emission reduction potential and mitigation cost[J]. Applied Energy, 2014, 124 (12): 82-93.
[4] GHANBARI H, PETTERSSON F, SAXEN H. Sustainable development of primary steelmaking under novel blast furnace operation and injection of different reducing agents[J]. Chemical Engineering Science, 2015, 129 (16): 1-32.
[5] 童力, 胡松涛, 罗思义. 高炉渣余热回收协同转化生物质制氢[J]. 化工学报, 2014, 65 (9): 3634-3639. TONG L, HU S T, LUO S Y. Waste heat recovery of blast furnace slag and utilization for production of hydrogen from biomass transformation[J]. CIESC Journal, 2014, 65 (9): 3634-3639.
[6] 卢虎生, 刘艳春. 钢铁企业铁精粉品味的边际冶炼价值分析[J]. 内蒙古科技大学学报, 2007, 26 (4): 32-39. LU H S, LIU Y C. Marginal metal logical value of iron contents in the concentrates of iron and steel company[J]. Journal of Inner Mongo, 2007, 26 (4): 32-39.
[7] CAO W C, ZHANG J L, ZHANG T, et al. A genetic algorithm application to minimize pig iron cost[J]. ISIJ International, 2013, 53 (2): 207-212.
[8] RASUL M G, TANTY B S, MOHANTY B. Modeling and analysis of blast furnace performance for efficient utilization of energy[J]. Applied Thermal Engineering, 2007, 27 (1): 78-88.
[9] 张琦, 姚彤辉, 蔡九菊. 高炉炼铁过程多目标优化模型的研究及应用[J]. 东北大学学报, 2011, 32 (2): 270-273. ZHANG Q, YAO T H, CAI J J. On the multiobjective optimal model of blast furnace iron-making process and its application[J]. Journal of Northeastern University, 2011, 32 (2): 270-273.
[10] LI H, ZHANG Q F. Multi-objective optimization problem with complicated pareto sets, MOEA/D and NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2009, 13 (2): 284-302.
[11] AUTUORI J, HNAIEN F, YALAOU F, et al. Comparison of solution space exploration by NSGA-Ⅱ and SPEA-Ⅱ for flexible job shop problem[J]. Control, Decision and Information Technologies Conference, 2013, 34 (2): 750-755.
[12] ASEFI H, JOLAI F, RABIEE M, et al. A hybrid NSGA-Ⅱ and VNS for solving a bi-objective no-wait flexible flow shop scheduling problem[J]. International Journal of Advanced Manufacturing Technology, 2014, 75 (5): 1017-1033.
[13] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multi-objective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6 (2): 182-197.
[14] HU C Q, HAN X W, LI Z H, et al. Comparison of CO2 emission between COREX and blast furnace iron-making system[J]. Journal of Environmental Sciences Supplement, 2009, 45 (1): 116-120.
[15] ZOU Z P, GUO X Z, WANG G, et al. Discussion of the calculation method of the BF's CO2 emission[J]. Journal of Iron and Steel Research, 2011, 27 (9): 59-64.
[16] PURWANTO H, KASAI E, AKIYAMA T. Process analysis of the effective utilization of molten slag heat by direct blast furnace cement production system[J]. ISIJ International, 2010, 50 (9): 1319-1325.
[17] ZHANG R J, LU J, ZHANG G Q. A knowledge-based multi-role decision support system for ore blending cost optimization of blast furnaces[J]. European Journal of Operational Research, 2011, 215 (1): 194-203.
[18] 张宇, 鄢烈祥, 李国建, 等. 非支配排序进化策略求解煤气化多目标优化问题[J]. 化工学报, 2013, 64 (12): 4628-4633. ZHANG Y, YAN L X, LI G J, et al. Multi-objective optimization of coal gasifier using NSES[J]. CIESC Journal, 2013, 64 (12): 4628-4633.
[19] 于晓栋, 吕文祥, 黄德先, 等. 基于HYSYS和NSGA-Ⅱ的常压塔多目标优化[J]. 化工学报, 2008, 59 (7): 1646-1649. YU X D, LÜ W X, HUANG D X, et al. Multi-objective optimization of industrial crude distillation unit based on HYSYS and NSGA-Ⅱ[J]. Journal of Chemical Industry and Engineering (China), 2008, 59 (7): 1646-1649.
[20] 吴献东, 金晓明, 苏宏业. 基于NSGA-Ⅱ的模拟移动床色谱分离过程多目标操作优化[J]. 化工学报, 2007, 58 (8): 2038-2044. WU X D, JIN X M, SU H Y. Multi-objective optimization of simulated moving bed chromatography separation based on NSGA-Ⅱ algorithm[J]. Journal of Chemical Industry and Engineering (China), 2007, 58 (8): 2038-2044.

[1] HAN Zhonghe, MEI Zhongkai, LI Peng. Working fluid selection and multi-objective optimization of organic Rankine cycle with variable turbine efficiency [J]. CIESC Journal, 2018, 69(6): 2603-2611.
[2] WANG Menghan, TU Shunli, YU Chunli. Optimization strategy of weld line assisted by air traps improvement based on Kriging and NSGA-Ⅱ [J]. CIESC Journal, 2018, 69(10): 4449-4455.
[3] YANG Deming, GU Qiang, ZHU Biyun, WANG Zhengguang, YIN Yifan, GAO Xiaoxin. MVR heat pump distillation process of mixed xylene based on organic Rankine cycle [J]. CIESC Journal, 2017, 68(12): 4641-4648.
[4] ZHAO Bo, YANG Shanrang, LIU Zhichao, CAO Shengxian. Cost estimation and optimal cleaning cycle optimization of ash fouling for air cooling condenser [J]. CIESC Journal, 2016, 67(9): 3927-3935.
[5] CHEN Jun, ZHOU Weiguo, WANG Hai, LI Su. Multi-objective optimal strategy for steam power system in steel industry based on electricity equivalent calculation [J]. CIESC Journal, 2016, 67(9): 3804-3811.
[6] QIAO Yudong, GAO Xin, LI Hong, LI Xingang. Life cycle cost evaluation of structured corrugation SiC-foam packing [J]. CIESC Journal, 2016, 67(8): 3459-3467.
[7] LU Yi, Edmund YAP, LIU Yirong, YUAN Xiaojun. Reliability,availability and maintainability(RAM)modeling to predict production performance of LNG storage terminal [J]. CIESC Journal, 2015, 66(S2): 430-438.
[8] LEI Qi, YAN Hui, WU Min. An on-line optimal control method for combustion process of coke oven based on multi-attribute performance evaluation [J]. CIESC Journal, 2015, 66(1): 307-315.
[9] LIU Zhexuan, QIU Tong, CHEN Bingzhen. Modeling and multi-objective optimization of multi-period biofuel supply chain [J]. CIESC Journal, 2014, 65(7): 2802-2812.
[10] XU Feng, JIANG Huirong, WANG Rui, LUO Xionglin. Tradeoff between whole margin and control performance for chemical process [J]. CIESC Journal, 2014, 65(4): 1303-1309.
[11] LIU Zhongliang1,WANG Yuanya1,ZHANG Kefang1,2,LI Yanxia1. Optimization and evaluation of flue gas processing systems based on pinch technology [J]. Chemical Industry and Engineering Progree, 2014, 33(10): 2801-2805.
[12] WU Shuangying, YI Tiantian, XIAO Lan. Parametric optimization and performance analysis of subcritical organic Rankine cycle based on multi-objective function [J]. CIESC Journal, 2014, 65(10): 4078-4085.
[13] ZHAO Wensheng,BAI Rui,WANG Jixuan,HAN Zhonghe,WANG Yingying. Analysis thermodynamic performances and techno-economic of solar coal-fired units based on carbon capture [J]. Chemical Industry and Engineering Progree, 2014, 33(05): 1338-1343.
[14] YANG Deming,YE Mengfei,DU Peng,GAO Xiaoxin. Research on technologies for separating ethanol and isopropanol based on the MVR heat-pump distillation [J]. Chemical Industry and Engineering Progree, 2014, 33(05): 1344-1347.
[15] SUN Honglei 1,Lü Jixing 2,HU Xuteng1,LI Jianzhong1,FU Xingguo1,HE Hao1. Cost-benefit analysis of application of aviation biofuel for airlines [J]. Chemical Industry and Engineering Progree, 2014, 33(05): 1151-1155.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!