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Research on Intelligent Predictive AGC of a Thermal Power Unit Based on Control Performance Standards

Author

Listed:
  • Daogang Peng

    (School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Yue Xu

    (School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Huirong Zhao

    (School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

Abstract

In order to satisfy the growing demands of control performance and operation efficiency in the automatic generation control (AGC) system of a grid, a novel, intelligent predictive controller, combined with predictive control and neural network ideas, is proposed and applied to the AGC systems of thermal power units. This paper proposes a Bayesian neural network identification model for typical ultra-supercritical thermal power units, which was found to be accurate and can be used as a simulation model. Based on the model, this paper develops an intelligent predictive control for the AGC of thermal power units, which improves unit load operation and constitutes a novel, closed-loop AGC structure based on online control performance standard (CPS) evaluations. Intelligent predictive control is mainly improved because the neural network rolling optimization model replaces the traditional rolling optimization model in the rolling optimization module. The simulation results indicate that the intelligent predictive controller developed in the two-area interconnected power grid under CPS can, on the one hand, improve the load tracking performance of AGC thermal power units, and, on the other hand, the controller has strong robustness. Whether the system parameters change considerably or the AGC has different grid disturbances, the new type of the loop AGC system can still sufficiently meet the control requirements of the power grid.

Suggested Citation

  • Daogang Peng & Yue Xu & Huirong Zhao, 2019. "Research on Intelligent Predictive AGC of a Thermal Power Unit Based on Control Performance Standards," Energies, MDPI, vol. 12(21), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:21:p:4073-:d:280275
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    References listed on IDEAS

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    1. Sreepradha, Chandrasekharan & Panda, Rames Chandra & Bhuvaneswari, Natrajan Swaminathan, 2017. "Mathematical model for integrated coal fired thermal boiler using physical laws," Energy, Elsevier, vol. 118(C), pages 985-998.
    2. Arya, Yogendra, 2019. "AGC of PV-thermal and hydro-thermal power systems using CES and a new multi-stage FPIDF-(1+PI) controller," Renewable Energy, Elsevier, vol. 134(C), pages 796-806.
    3. Zhang, Shirong & Mao, Wei, 2017. "Optimal operation of coal conveying systems assembled with crushers using model predictive control methodology," Applied Energy, Elsevier, vol. 198(C), pages 65-76.
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