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在钢铁生产过程中,消耗的煤炭大约34%会转化为副产煤气。为了提高副产煤气能源利用率,以钢铁企业副产煤气系统为研究对象,利用混合整数线性规划法(mixed integer linear programming,MILP),以操作成本最小化为目标函数,以物料平衡、能量平衡、设备操作参数限制等为约束条件建立富余煤气优化调度模型。与前人的模型相比,对锅炉模型进行改进,不仅提高锅炉模型的调节精度,而且更接近实际情况。此外,为了研究煤气柜和锅炉稳定性,引入煤气柜总标准偏移量(sum of standard deviation volume,SSDV)惩罚因子和锅炉总改变量(sum of switching percentage,SSP)惩罚因子,并用帕雷托最优法理论确定出最佳的SSDV 和SSP。结果表明,新的优化模型能很好地降低煤气柜和锅炉的波动,维持煤气系统的平稳运行。

In iron and steel production,around 34%of the coal energy is converted into byproduct gases. In order to im-prove the energy efficiency of byproduct gas,the current study proposed an improved mixed integer linear programming (MILP)model which treated the minimum of operation cost as the objective function and regarded the mass balance, the energy and the operation parameters as the constraint conditions,to optimize byproduct gas distribution in a steel plant in China. Compared with previous models,this model improved the adjustment accuracy of the boiler model which would reflect the real operation better. Since the most important thing in the byproduct gas scheduling is to sustain the stability of the whole system,the current study defined the sum of standard deviation volume(SSDV)and sum of switching percentage(SSP)to evaluate the stability of gasholders and boilers,and Pareto optimality was applied to se-lect reasonable penalty factors. Calculation results demonstrate that compared with manual operation,the planning of the optimal distribution of byproduct gases proposed in this study can reduce the fluctuation of the gasholders and the load of the boilers to make the operation of the byproduct gas system safe and stable.

参考文献

[1] 张琦 .钢铁联合企业煤气资源合理利用及优化分配研究[D].东北大学,2008.
[2] 郦秀萍;张春霞;黄导;周继程;上官方钦.GB 21256-2013《粗钢生产主要工序单位产品能源消耗限额》标准解读与实施建议[J].中国冶金,2016(3):47-52,61.
[3] 高成康;陈杉;陈胜;秦威.中国典型钢铁联合企业的碳足迹分析[J].钢铁,2015(3):1-8.
[4] J.H.Kim;H.-S.Yi;C.Han.A novel milp Model for Plantwide Multiperiod optimization of byproduct gas supply system in the iron- and steel-making process[J].Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers,2003A8(A8):1015-1025.
[5] 张建良;王妤.钢铁企业煤气系统的优化利用模型[J].包头钢铁学院学报,2002(3):280-282.
[6] 张琦;蔡九菊;杜涛.钢铁联合企业煤气系统优化利用[J].冶金能源,2005(5):9-11,16.
[7] An MILP model for optimization of byproduct gases in the integrated iron and steel plant[J].Applied energy,20107(7):P.2156.
[8] 孔海宁 .钢铁企业副产煤气系统优化高度研究[D].天津大学,2011.
[9] 张琦;提威;杜涛;蔡九菊.钢铁企业富余煤气-蒸汽-电力耦合模型及其应用[J].化工学报,2011(3):753-758.
[10] 赵贤聪;白皓;李宏煦;王超;郑龙山;韩杰海.钢铁生产过程富余煤气动态优化分配模型[J].北京科技大学学报,2015(1):97-105.
[11] Zhao, Xiancong;Bai, Hao;Lu, Xin;Shi, Qi;Han, Jiehai.A MILP model concerning the optimisation of penalty factors for the short-term distribution of byproduct gases produced in the iron and steel making process[J].Applied energy,2015Jun.15(Jun.15):142-158.
[12] 孟华;王建军;王华;李红娟.重审钢铁企业煤气系统不平衡问题[J].钢铁,2015(3):84-90,95.
[13] 李红娟;王建军;王华;孟华.基于HP-Elman-LSSVM模型钢铁企业自备电厂煤气供入量预测及优化调度[J].钢铁,2013(8):75-81.
[14] 陈林根;杨博;谢志辉;王文华;孙丰瑞.转炉煤气驱动开式燃气轮机CCHP装置FTT建模与优化[J].中国冶金,2014(5):50-58.
[15] Sumit Mitra;Lige Sun;Ignacio E. Grossmann.Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices[J].Energy,2013Jun.(Jun.):194-211.
[16] 胡蓉;杨明磊;钱锋.基于多目标教学优化算法在二甲苯吸附分离过程优化中的应用[J].化工学报,2015(1):326-332.
[17] 许锋;蒋慧蓉;王锐;罗雄麟.化工过程总体裕量与控制性能的权衡优化[J].化工学报,2014(4):1303-1309.
[18] Luo, Xianglong;Hu, Jiahao;Zhao, Jun;Zhang, Bingjian;Chen, Ying;Mo, Songping.Multi-objective optimization for the design and synthesis of utility systems with emission abatement technology concerns[J].Applied energy,2014Dec.31(Dec.31):1110-1131.
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