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Closed-Loop Combustion Optimization Based on Dynamic and Adaptive Models with Application to a Coal-Fired Boiler

Author

Listed:
  • Chuanpeng Zhu

    (National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China
    Shenhua Guohua (Shouguang) Thermal Power Co., Ltd., Shouguang 262714, China)

  • Pu Huang

    (National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Yiguo Li

    (National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China)

Abstract

To increase combustion efficiency and reduce pollutant emissions, this study presents an online closed-loop optimization method and its application in a boiler combustion system. To begin with, three adaptive dynamic models are established to predict NOx emission, the carbon content of fly ash (Cfh), and exhaust gas temperature (Teg), respectively. In these models, the orders of the input variables are considered to enable them to reflect the dynamics of the combustion system under load changes. Meanwhile, an adaptive least squares support vector machine (ALSSVM) algorithm is adopted to cope with the nonlinearity and the time-varying characteristics of the combustion system. Subsequently, based on the established models, an economic model predictive control (EMPC) problem is formulated and solved by a sequential quadratic programming (SQP) algorithm to calculate the optimal control variables satisfying the constraints on the control and control moves. The closed-loop optimization system is applied on a 600 MW boiler, and the performance analysis is conducted based on the operation data. The results show that the system can effectively increase boiler efficiency by about 0.5%.

Suggested Citation

  • Chuanpeng Zhu & Pu Huang & Yiguo Li, 2022. "Closed-Loop Combustion Optimization Based on Dynamic and Adaptive Models with Application to a Coal-Fired Boiler," Energies, MDPI, vol. 15(14), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5289-:d:868375
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    References listed on IDEAS

    as
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