• DocumentCode
    2481115
  • Title

    Hybrid modeling and optimal control of Wet Flue Gas Desulphurization process

  • Author

    Shi, Yuntao ; Sun, Dehui ; Li, Zhijun ; Gao, Dongjie

  • Author_Institution
    Key Lab. of Field Bus & Autom. of Beijing, North China Univ. of Technol., Beijing
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    1846
  • Lastpage
    1851
  • Abstract
    The optimization and control problem of wet flue gas desulphurization in power plant was studied. Mixed logical dynamics model was built to describe hybrid phenomenon of the WFGD process. Based on the mixed logic dynamics model of WFGD, the predictive control optimization problem was solved using the Mixed Integer Quadratic program (MIQP) solver. Therefore the optimal discrete decision variable (the number of LG pump) and the continuous variable decision variable (PH set-point) were obtained on line. The real-time optimization was implemented. A MLD model of PH was also developed based on which the predictive controller of PH was designed. The simulation results indicate that the predictive control based on MLD model scheme presented has good effect.
  • Keywords
    flue gas desulphurisation; integer programming; optimal control; power generation control; predictive control; quadratic programming; mixed integer quadratic program; mixed logical dynamics model; optimal control; optimal discrete decision variable; power plant; predictive control optimization problem; wet flue gas desulphurization process; Automation; Bismuth; Flue gases; Intelligent control; Logic; Optimal control; Power generation; Predictive control; Predictive models; US Department of Energy; mixed integer quadratic program; mixed logical dynamics; predictive control; wet flue gas desulphurization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593204
  • Filename
    4593204