SCI和EI收录∣中国化工学会会刊

中国化学工程学报 ›› 2023, Vol. 54 ›› Issue (2): 343-352.DOI: 10.1016/j.cjche.2022.03.014

• Full Length Article • 上一篇    下一篇

Multiobjective economic model predictive control using utopia-tracking for the wet flue gas desulphurization system

Shan Liu, Wenqi Zhong, Xi Chen, Li Sun, Lukuan Yang   

  1. Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China
  • 收稿日期:2021-10-12 修回日期:2022-03-03 出版日期:2023-02-28 发布日期:2023-05-11
  • 通讯作者: Wenqi Zhong,E-mail:wqzhong@seu.edu.cn
  • 基金资助:
    This work was supported by the National Key Research and Development Program of China (2017YFB0601805). Special thanks to Datang Environment Industry Group Co., Ltd. for providing data.

Multiobjective economic model predictive control using utopia-tracking for the wet flue gas desulphurization system

Shan Liu, Wenqi Zhong, Xi Chen, Li Sun, Lukuan Yang   

  1. Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China
  • Received:2021-10-12 Revised:2022-03-03 Online:2023-02-28 Published:2023-05-11
  • Contact: Wenqi Zhong,E-mail:wqzhong@seu.edu.cn
  • Supported by:
    This work was supported by the National Key Research and Development Program of China (2017YFB0601805). Special thanks to Datang Environment Industry Group Co., Ltd. for providing data.

摘要: Efficient control of the desulphurization system is challenging in maximizing the economic objective while reducing the SO2 emission concentration. The conventional optimization method is generally based on a hierarchical structure in which the upper optimization layer calculates the steady-state results and the lower control layer is responsible to drive the process to the target point. However, the conventional hierarchical structure does not take the economic performance of the dynamic tracking process into account. To this end, multi-objective economic model predictive control (MOEMPC) is introduced in this paper, which unifies the optimization and control layers in a single stage. The objective functions are formulated in terms of a dynamic horizon and to balance the stability and economic performance. In the MOEMPC scheme, economic performance and SO2 emission performance are guaranteed by tracking a set of utopia points during dynamic transitions. The terminal penalty function and stabilizing constraint conditions are designed to ensure the stability of the system. Finally, an optimized control method for the stable operation of the complex desulfurization system has been established. Simulation results demonstrate that MOEMPC is superior over another control strategy in terms of economic performance and emission reduction, especially when the desulphurization system suffers from frequent flue gas disturbances.

关键词: Desulphurization system, Economics, Economic model predictive control, Flue gas, Optimization, Utopia point

Abstract: Efficient control of the desulphurization system is challenging in maximizing the economic objective while reducing the SO2 emission concentration. The conventional optimization method is generally based on a hierarchical structure in which the upper optimization layer calculates the steady-state results and the lower control layer is responsible to drive the process to the target point. However, the conventional hierarchical structure does not take the economic performance of the dynamic tracking process into account. To this end, multi-objective economic model predictive control (MOEMPC) is introduced in this paper, which unifies the optimization and control layers in a single stage. The objective functions are formulated in terms of a dynamic horizon and to balance the stability and economic performance. In the MOEMPC scheme, economic performance and SO2 emission performance are guaranteed by tracking a set of utopia points during dynamic transitions. The terminal penalty function and stabilizing constraint conditions are designed to ensure the stability of the system. Finally, an optimized control method for the stable operation of the complex desulfurization system has been established. Simulation results demonstrate that MOEMPC is superior over another control strategy in terms of economic performance and emission reduction, especially when the desulphurization system suffers from frequent flue gas disturbances.

Key words: Desulphurization system, Economics, Economic model predictive control, Flue gas, Optimization, Utopia point