汤 伟,孙振宇,池东明,冯晓会.高强瓦楞纸机干燥部能耗协同控制系统的设计及优化研究[J].中国造纸学报,2017,32(3):58-63 本文二维码信息
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高强瓦楞纸机干燥部能耗协同控制系统的设计及优化研究
Design and Optimization of Synergic Control System for Energy Consumption of High Strength Fluting Paper Machine Dryer Section
  
DOI:10.11981/j.issn.1000-6842.2017.03.58
中文关键词:  蒸汽冷凝水热力系统  密闭气罩热力系统  能耗协同控制  DCS控制系统  数据驱动
Key Words:steam condensate thermal system  hood ventilation thermal system  cooperation control for energy consumption  DCS control system  data-driven
基金项目:陕西省重点科技创新团队计划项目(2014KCT-15);咸阳市科技计划项目(2012K03-01);陕西省教育厅重点实验室科研计划项目(15JS013)。
作者单位
汤 伟1,3 1.陕西科技大学电气与信息工程学院陕西西安,7100213.陕西科技大学工业自动化研究所陕西西安,710021 
孙振宇2,3 2.陕西科技大学轻工科学与工程学院陕西西安,7100213.陕西科技大学工业自动化研究所陕西西安,710021 
池东明2,3 2.陕西科技大学轻工科学与工程学院陕西西安,7100213.陕西科技大学工业自动化研究所陕西西安,710021 
冯晓会1,3 1.陕西科技大学电气与信息工程学院陕西西安,7100213.陕西科技大学工业自动化研究所陕西西安,710021 
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中文摘要:
      为了进一步地降低纸机干燥部能耗、提高能源的利用效率,本课题提出了能耗协同控制的概念,即同时考虑烘缸内部蒸汽冷凝水热力系统的能量消耗与气罩通风热力系统的能量消耗,实现二次热能的循环综合利用。针对高强瓦楞纸机干燥部设计了一套基于西门子S7-300 PLC的能耗协同DCS控制系统,实现了干燥部上述系统的整合,不但能够降低纸机干燥部的能耗,也为干燥部全局优化方案的实现打下了基础。本控制系统已在多条高强瓦楞纸机生产线上得到了应用,收到了较好的节能效果。为了实现干燥部的全局优化,本课题搭建了基于数据驱动的控制策略优化控制框架,将工业现场的大量运行数据用于模型的修正并建立控制策略优化数据库,可以快速寻找与当前工艺条件最为匹配的优化控制策略,实现节能降耗。
Abstract:
      Energy consumption reduction is becoming focus in papermaking industry. To further reduce energy consumption and increase energy efficiency of paper machine dryer section, the synergic control for energy consumption was put forward. The energy consumptions of steam condensate thermal system and hood ventilation thermal system were considered together to recycle the secondary thermal energy. A DCS control system for energy consumption of high strength fluting paper machine was designed. This system integrated above-mentioned systems, not only reduced the energy consumption of paper machine dryer section but also laid a foundation for achieving overall optimization of dryer section. This control system has been used in many high strength fluting paper machines and had a better energy-saving effect. To achieve overall optimization of dryer section, the data-driven optimization control framework was designed. The large amount of operation data was used to update the model and established the optimal control strategy database. Thus the optimization control strategy which matched current process conditions best could be found quickly, and energy consumption reduction was realized.
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