·292· 工程科学学报，第39卷，第2期 tems.Cancun,2007:279 7 ◇-缓冲容量=113500m3 [6] Glankwamdee W,Linderoth J,Shen J R,et al.Combining opti- o一缓冲容量-103500m3 -△-缓冲容量=93500m3 mization and simulation for strategic and operational industrial gas 5 0-缓冲容量-83500m3 production and distribution.Comput Chem Eng,2008,32(11): 2536 4 [7]Mitra S,Grossmann I E,Pinto J M,et al.Optimal production planning under time-sensitive electricity prices for continuous pow- 24 er-intensive processes.Comput Chem Eng,2012,38:171 [8]Manenti F,Bozzano G,D'Isanto M,et al.Raising the decision- 0681920222232425262.72.82930 making level to improve the enterprise-wide production flexibility. 高压管网初始压力MPa A1ChEJ,2013,59(5):1588 [9] Manenti F.Rovaglio M.Market-driven operational optimization of 图11不同缓冲容量下高压管网初始压力对氧气总放散率的影 industrial gas supply chains.Comput Chem Eng,2013,56:128 响规律 [10]Mitra S,Pinto J M,Grossmann I E.Optimal multi-scale capacity Fig.11 Influence of the initial pressure of high-pressure networks on planning for power-intensive continuous processes under time- the optimized results of oxygen emission ratio under different buffer ca- sensitive electricity prices and demand uncertainty:Part I.Mod- pacities elling.Comput Chem Eng,2014,65:89 [11]Mitra S,Pinto J M,Grossmann I E.Optimal multi-scale capacity 3结论 planning for power-intensive continuous processes under time- sensitive electricity prices and demand uncertainty:Part II.En- (1)针对钢铁企业空分厂氧气系统建立的混合整 hanced hybrid bi-level decomposition.Comput Chem Eng, 数线性规划(mixed integer linear program,MLP)模型 2014.65:102 可对氧气生产进行合理有效调度. [12]Marchetti PA,Gupta V,Grossmann I E,et al.Simultaneous (2)高压管网初始压力越低，休风时期的缓冲能 production and distribution of industrial gas supply-chains. 力越强，降低初始压力对降低放散率效果显著.因此 Comput Chem Eng,2014,69:39 在高炉休风来临之前，设法降低高压管网压力对降低 [13]Rossi F,Manenti F,Reklaitis G.A general modular framework for the integrated optimal management of an industrial gases sup- 放散率十分重要. ply-chain and its production systems.Comput Chem Eng,2015, (3)高压管网初始压力大于临界值时，系统出现 82:84 氧气放散，放散率随初始压力上升呈线性关系增大，高 [14]Zhang Q,Sundaramoorthy A,Grossmann IE,et al.A discrete- 压管网缓冲容量越大，该线性关系斜率越大 time scheduling model for continuous power-intensive process (4)有氧气放散的情况下，对于同一高压管网初 networks with various power contracts.Comput Chem Eng, 始压力，高压管网缓冲容量越大，系统放散率越小.该 2016,84:382 趋势随着高压管网初始压力增大变得越来越不明显， [15]Liu Z,Tang X Z,Zhao L H.R&D on oxygen rational utilization system in iron and steel enterprises.Energ Metall Ind,1998,17 当初始压力等于最高压力时，高压管网缓冲容量的大 (6):6 小对放散率没有影响. (刘姿，汤学忠，赵立合.钢铁企业氧气合理利用支持系统 的开发研究.治金能源，1998,17(6)：6) 参考文献 [16]Tong L G,Wang L,Tang X Z.et al.Model of blast fumnace [1]Li H Z.Oxygen Technology.2nd Ed.Beijing:Metallurgical In- blow down for oxygen releasing rate.Energ Metall Ind,1999,18 dustry Press,2009 (3):16 (李化治.制氧技术.2版.北京：冶金工业出版社.2009) (童莉葛，王立，汤学忠，等.降低氧气放散率的高炉休风 [2]Fu Q,Kansha Y,Song C F,et al.A cryogenic air separation 模型.冶金能源，1999,18(3)：16) process based on self-heat recuperation for oxy-combustion plants. [17]Chen G.Lu Z W,Cai JJ,et al.Dynamic simulation of oxygen 4 opl Energ,2016,162:1114 supply system in iron and steel company.I Northeast Unie Nat [3]Xu Z H,Zhao J,Chen X,et al.Automatic load change system of Sci,2002,23(10):940 cryogenic air separation process.Sep Purif Technol,2011,81 (陈光，陆钟武，蔡九菊，等.钢铁企业氧气系统动态仿真 (3):451 东北大学学报（自然科学版），2002,23(10)：940) [4]Manenti F,Manca D.Transients modelling for enterprise-wide op- [18]Mo Y K.Research about the Decision Support System of Iron and timization:Generalized framework and industrial case study. Steel Enterprise Optimum Oxygen Supply [Dissertation].Wuhan: Chem Eng Res Des,2009,87(8):1028 Huazhong University of Science Technology,2004 [5]Manenti F.Rovaglio M.Operational planning in the management (莫友坤.钢铁企业供氧优化决策支持系统研究[学位论 of programmed maintenances-a MILP approach/Proceedings of 文].武汉：华中科技大学，2004) the 8th IFAC Symposium on Dynamies and Control of Process Sys- [19]Yang J B.A Research on the Decision Analysis and Optimization工程科学学报,第 39 卷,第 2 期 图 11 不同缓冲容量下高压管网初始压力对氧气总放散率的影 响规律 Fig. 11 Influence of the initial pressure of high鄄pressure networks on the optimized results of oxygen emission ratio under different buffer ca鄄 pacities 3 结论 (1)针对钢铁企业空分厂氧气系统建立的混合整 数线性规划( mixed integer linear program, MILP) 模型 可对氧气生产进行合理有效调度. (2)高压管网初始压力越低,休风时期的缓冲能 力越强,降低初始压力对降低放散率效果显著. 因此 在高炉休风来临之前,设法降低高压管网压力对降低 放散率十分重要. (3)高压管网初始压力大于临界值时,系统出现 氧气放散,放散率随初始压力上升呈线性关系增大,高 压管网缓冲容量越大,该线性关系斜率越大. (4)有氧气放散的情况下,对于同一高压管网初 始压力,高压管网缓冲容量越大,系统放散率越小. 该 趋势随着高压管网初始压力增大变得越来越不明显, 当初始压力等于最高压力时,高压管网缓冲容量的大 小对放散率没有影响. 参 考 文 献 [1] Li H Z. Oxygen Technology. 2nd Ed. Beijing: Metallurgical In鄄 dustry Press, 2009 (李化治. 制氧技术. 2 版. 北京: 冶金工业出版社, 2009) [2] Fu Q, Kansha Y, Song C F, et al. A cryogenic air separation process based on self鄄heat recuperation for oxy鄄combustion plants. Appl Energy, 2016, 162: 1114 [3] Xu Z H, Zhao J, Chen X, et al. Automatic load change system of cryogenic air separation process. Sep Purif Technol, 2011, 81 (3): 451 [4] Manenti F, Manca D. Transients modelling for enterprise鄄wide op鄄 timization: Generalized framework and industrial case study. Chem Eng Res Des, 2009, 87(8): 1028 [5] Manenti F, Rovaglio M. Operational planning in the management of programmed maintenances鄄a MILP approach / / Proceedings of the 8th IFAC Symposium on Dynamics and Control of Process Sys鄄 tems. Canc俨n, 2007: 279 [6] Glankwamdee W, Linderoth J, Shen J R, et al. Combining opti鄄 mization and simulation for strategic and operational industrial gas production and distribution. Comput Chem Eng, 2008, 32(11): 2536 [7] Mitra S, Grossmann I E, Pinto J M, et al. Optimal production planning under time鄄sensitive electricity prices for continuous pow鄄 er鄄intensive processes. Comput Chem Eng, 2012, 38: 171 [8] Manenti F, Bozzano G, D蒺Isanto M, et al. Raising the decision鄄 making level to improve the enterprise鄄wide production flexibility. AIChE J, 2013, 59(5): 1588 [9] Manenti F, Rovaglio M. Market鄄driven operational optimization of industrial gas supply chains. Comput Chem Eng, 2013, 56: 128 [10] Mitra S, Pinto J M, Grossmann I E. Optimal multi鄄scale capacity planning for power鄄intensive continuous processes under time鄄 sensitive electricity prices and demand uncertainty: Part I. Mod鄄 elling. Comput Chem Eng, 2014, 65: 89 [11] Mitra S, Pinto J M, Grossmann I E. Optimal multi鄄scale capacity planning for power鄄intensive continuous processes under time鄄 sensitive electricity prices and demand uncertainty: Part II. En鄄 hanced hybrid bi鄄level decomposition. Comput Chem Eng, 2014, 65: 102 [12] Marchetti P A, Gupta V, Grossmann I E, et al. Simultaneous production and distribution of industrial gas supply鄄chains. Comput Chem Eng, 2014, 69: 39 [13] Rossi F, Manenti F, Reklaitis G. A general modular framework for the integrated optimal management of an industrial gases sup鄄 ply鄄chain and its production systems. Comput Chem Eng, 2015, 82: 84 [14] Zhang Q, Sundaramoorthy A, Grossmann I E, et al. A discrete鄄 time scheduling model for continuous power鄄intensive process networks with various power contracts. Comput Chem Eng, 2016, 84: 382 [15] Liu Z, Tang X Z, Zhao L H. R&D on oxygen rational utilization system in iron and steel enterprises. Energ Metall Ind, 1998, 17 (6): 6 (刘姿, 汤学忠, 赵立合. 钢铁企业氧气合理利用支持系统 的开发研究. 冶金能源, 1998, 17(6): 6) [16] Tong L G, Wang L, Tang X Z, et al. Model of blast furnace blow down for oxygen releasing rate. Energ Metall Ind, 1999, 18 (3): 16 (童莉葛, 王立, 汤学忠, 等. 降低氧气放散率的高炉休风 模型. 冶金能源, 1999, 18(3): 16) [17] Chen G, Lu Z W, Cai J J, et al. Dynamic simulation of oxygen supply system in iron and steel company. J Northeast Univ Nat Sci, 2002, 23(10): 940 (陈光, 陆钟武, 蔡九菊, 等. 钢铁企业氧气系统动态仿真. 东北大学学报 (自然科学版), 2002, 23(10): 940) [18] Mo Y K. Research about the Decision Support System of Iron and Steel Enterprise Optimum Oxygen Supply [Dissertation]. Wuhan: Huazhong University of Science & Technology, 2004 (莫友坤. 钢铁企业供氧优化决策支持系统研究[学位论 文]. 武汉: 华中科技大学, 2004) [19] Yang J B. A Research on the Decision Analysis and Optimization ·292·