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基于能量流网络仿真的钢铁工业多能源介质优化调配

孙彦广 梁青艳 李文兵 贾天云

孙彦广, 梁青艳, 李文兵, 贾天云. 基于能量流网络仿真的钢铁工业多能源介质优化调配. 自动化学报, 2017, 43(6): 1065-1079. doi: 10.16383/j.aas.2017.c170184
引用本文: 孙彦广, 梁青艳, 李文兵, 贾天云. 基于能量流网络仿真的钢铁工业多能源介质优化调配. 自动化学报, 2017, 43(6): 1065-1079. doi: 10.16383/j.aas.2017.c170184
SUN Yan-Guang, LIANG Qing-Yan, LI Wen-Bing, JIA Tian-Yun. Steel Industry Multi-type Energy Optimized Scheduling with Energy Flow Network Simulation. ACTA AUTOMATICA SINICA, 2017, 43(6): 1065-1079. doi: 10.16383/j.aas.2017.c170184
Citation: SUN Yan-Guang, LIANG Qing-Yan, LI Wen-Bing, JIA Tian-Yun. Steel Industry Multi-type Energy Optimized Scheduling with Energy Flow Network Simulation. ACTA AUTOMATICA SINICA, 2017, 43(6): 1065-1079. doi: 10.16383/j.aas.2017.c170184

基于能量流网络仿真的钢铁工业多能源介质优化调配

doi: 10.16383/j.aas.2017.c170184
基金项目: 

国家高技术研究发展计划(863计划) 2013BAE07B01

详细信息
    作者简介:

    梁青艳 钢铁研究总院博士研究生.2009年获得冶金自动化研究设计院控制理论与控制工程工学硕士学位.主要研究方向为钢铁行业能源管理与优化.E-mail:liang-qingyan@163.com

    李文兵 冶金自动化研究设计院教授级高工.2009年获得北京科技大学控制理论与控制工程工学博士学位.主要研究方向为工业信息化和工业流程仿真.E-mail:li-wenbing@126.com

    贾天云 冶金自动化研究设计院高级工程师.2009年获得冶金自动化研究设计院控制理论与控制工程工学硕士学位.主要研究方向为工业信息化和工业能源管理.E-mail:jiatianyun224@163.com

    通讯作者:

    孙彦广 冶金自动化研究设计院教授级高工.1990年获得中国科学院自动化所工学博士学位.主要研究方向为复杂工业过程建模和智能控制, 钢铁企业能源动态调控, 物质流能量流协同优化.E-mail:syanguang@263.net

Steel Industry Multi-type Energy Optimized Scheduling with Energy Flow Network Simulation

Funds: 

National Basic Research Program of China (863 Program) 2013BAE07B01

More Information
    Author Bio:

    Ph. D. candidate at the Central Iron & Steel Research Institute. She received her master degree in technical science from Automation Research and Design Institute of Metallurgical Industry in 2009. Her research interest covers energy management and optimization in iron and steel industry

    Professorate senior engineer at Automation Research and Design Institute of Metallurgical Industry. She received her Ph. D. degree in technical science degree from University of Science and Technology Beijing in 2009. Her research interest covers industrial informationization and industrial process simulation

    Senior engineer at Automation Research and Design Institute of Metallurgical Industry. He received his master degree in technical science degree from Automation Research and Design Institute of Metallurgical Industry in 2009. His research interest covers industrial informationization and industrial energy saving

    Corresponding author: SUN Yan-Guang Professorate senior engineer at Automation Research and Design Institute of Metallurgical Industry. He received his Ph. D. degree in technical science from Institute of Automation, Chinese Academy of Sciences in 1990. His research interest covers complex industrial process modeling and intelligent control, energy regulation and control of iron and steel enterprises, material flow and energy flow collaborative optimization. Corresponding author of this paper
  • 摘要: 钢铁工业发展面临能源的严重制约,能源优化调配是钢铁企业系统节能的关键技术之一.从钢铁制造流程物质流能量流耦合特点出发,首先,探讨了基于能量流网络仿真的钢铁工业多能源介质综合优化调配策略;然后,探讨了能量流网络化建模、生产流程与能源系统结合的能源仿真、多能源介质综合优化调配技术;最后,给出了在钢铁企业示范应用的效果.
    1)  本文责任编委 王伟
  • 图  1  能量流网络模型的信息流与控制

    Fig.  1  Information flow and control of energy flow network model

    图  2  钢铁企业能量流网络集成模型结构框图

    Fig.  2  Structural block diagram of energy flow network integration model for iron and steel enterprises

    图  3  高炉工序与能量流网络模型集成

    Fig.  3  Blast furnace process and energy flow network model integration

    图  4  电力能量流网络与其他介质能量流网络集成

    Fig.  4  Power energy flow network and other media energy flow network integration

    图  5  基于能量流网络模型的能源系统动态仿真

    Fig.  5  Dynamic simulation of energy system based on energy flow network model

    图  6  介质之间优先级依赖关系

    Fig.  6  Priority dependencies between media

    图  7  煤气的调配规则及各类负荷分配次序

    Fig.  7  Gas distribution rules and various types of load distribution order

    图  8  某钢铁企业一段时间内煤气和电力供需平衡情况

    Fig.  8  Gas and electricity supply and demand balance in a period of time in a steel enterprise

    图  9  基于能源仿真的多能源介质综合优化调配流程

    Fig.  9  Comprehensive optimization of multi-energy medium based on energy simulation

    图  10  某钢铁企业煤气-蒸汽-电力系统示意图

    Fig.  10  A diagram of a gas-steam-electric power system in a steel enterprise

    图  11  各周期系统运行费用优化前后对比

    Fig.  11  Comparison of system operating costs of each cycle before and after optimization

    表  1  各时段富余煤气供应及蒸汽和电力需求

    Table  1  Wealthy gas supply and steam and electricity demand for each period

    时段BFG (km3/h)COG (km3/h)电(MW)S1 (t/h)S2 (t/h)S3 (t/h)
    1535.5153.53706.2868.04232.0272.88
    2559.0454.92695.7265.46233.6386.54
    3596.7253.19687.0768.50244.1086.51
    4601.0854.33688.2168.00241.6587.06
    5603.8150.49683.9169.29232.4687.34
    6591.3441.40692.7066.46227.0975.43
    7519.2241.01687.9267.75212.8688.88
    8535.5739.67671.7168.88222.1092.51
    9551.9137.43645.1468.46231.1995.83
    10485.5829.66621.2867.25223.9895.74
    11450.5329.85606.1568.25213.3196.46
    12434.8341.19590.3269.25211.2395.31
    13526.8749.38598.7563.96210.0196.10
    14574.0951.22588.7264.46207.6895.13
    15575.1250.32580.6364.96211.2694.86
    16579.0650.39590.4066.46208.8394.80
    17585.3249.34614.2667.41204.7594.98
    18490.6549.33627.6365.41204.2095.43
    19465.1150.53630.0964.58204.9596.00
    20479.2945.10633.6868.68204.0795.14
    21555.1142.69639.9268.67199.9995.60
    22588.4642.71661.8768.17210.3995.31
    23583.3044.64665.5167.67207.1194.44
    24544.3247.94672.4966.00216.0890.16
    下载: 导出CSV

    表  2  正常工况优化前后各种费用比较

    Table  2  Comparison of various costs in normal working conditions before and after optimization

    费用优化前优化后
    外购煤费用(万元)233.6498234.1791
    外购天然气费用(万元)00
    给水费用(万元)7.51277.6305
    缓冲用户煤气使用费用(万元)122.0902123.1707
    外购电费用(万元)23.86389.18634
    外送电收益(万元)10.640118.7683
    设备运行维护费用(万元)98.9796101.4965
    总费用(万元)475.4562456.8951
    放散率00
    下载: 导出CSV

    表  3  电网电价

    Table  3  Grid price

    时段时间外购电价(元/kWh)外送电价(元/kWh)
    峰时段8:00~11:00和19:00~23:000.71880.3394
    平时段7:00~8:00和11:00~19:000.49170.3394
    谷时段0:00~7:00和23:00~24:000.27960.3394
    下载: 导出CSV

    表  4  铁钢系统减产10小时工况优化前后各种费用对比

    Table  4  The comparison of various costs for 10 hour reduction of the steel system before and after optimization

    费用优化前优化后
    外购煤费用(万元)253.68205.82
    外购天然气费用(万元)2.585.78
    缓冲用户煤气使用费用(万元)100.1597.5
    外购电费用(万元)36.3237.56
    外送电收益(万元)080.07
    设备运行维护费用(万元)82.2282.04
    总费用(万元)474.96348.64
    放散率00
    下载: 导出CSV

    表  5  2 250轧线停产12小时工况优化前后各种费用对比

    Table  5  The comparison of various costs for 12 hours cut ofi of 2 250 rolling line before and after the optimization

    费用优化前优化后
    外购煤费用(万元)213.17193.497
    外购天然气费用(万元)2.412.38
    缓冲用户煤气使用费用(万元)118.6396.119
    外购电费用(万元)29.1738.84
    外送电收益(万元)024.69
    设备运行维护费用(万元)81.7381.23
    总费用(万元)445.13387.388
    放散率00
    下载: 导出CSV
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出版历程
  • 收稿日期:  2017-04-06
  • 录用日期:  2017-05-11
  • 刊出日期:  2017-06-20

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