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Multi-Objective Intelligent Optimization of Superheated Steam Temperature Control Based on Cascaded Disturbance Observer

Author

Listed:
  • Yong-Sheng Hao

    (Key Lab of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Zhuo Chen

    (Key Lab of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Li Sun

    (Key Lab of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Junyu Liang

    (Yunnan Electric Power Research Institute, CSG, Kunming 650000, China)

  • Hongxia Zhu

    (School of Energy and Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

Abstract

Superheated steam temperature (SST) is one of the most critical parameters for the process safety, overall efficiency and pollution reduction of coal-fired power plants. However, SST control is challenging due to various disturbances and model uncertainties, especially in the face of the growing penetration of intermittent renewable energy into the power grid. To this end, a cascaded Disturbance Observer-PI (DOB-PI) control strategy is proposed to enhance control performance. The observer design and parameter tuning are carried out through mechanism analysis on the proposed structure. Furthermore, a robust loop shaping method is introduced as a hard constraint to balance the control performance and robustness. The controller parameters are optimized based on the multi-objective artificial bee colony optimization (MOABC) algorithm. Simulation results show that the proposed cascaded DOB-PI control strategy can significantly improve the disturbance rejection performance of both the inner- and outer-loops of the SST control system. This paper indicates promising prospects for the proposed method in future applications.

Suggested Citation

  • Yong-Sheng Hao & Zhuo Chen & Li Sun & Junyu Liang & Hongxia Zhu, 2020. "Multi-Objective Intelligent Optimization of Superheated Steam Temperature Control Based on Cascaded Disturbance Observer," Sustainability, MDPI, vol. 12(19), pages 1-24, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8235-:d:424369
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    References listed on IDEAS

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    1. Sun, Li & Jin, Yuhui & You, Fengqi, 2020. "Active disturbance rejection temperature control of open-cathode proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 261(C).
    2. Fang, Fang & Wei, Le, 2011. "Backstepping-based nonlinear adaptive control for coal-fired utility boiler-turbine units," Applied Energy, Elsevier, vol. 88(3), pages 814-824, March.
    3. Xiao Wu & Jiong Shen & Yiguo Li & Kwang Y. Lee, 2015. "Steam power plant configuration, design, and control," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 4(6), pages 537-563, November.
    4. Wu, Zhenlong & Li, Donghai & Xue, Yali & Chen, YangQuan, 2019. "Gain scheduling design based on active disturbance rejection control for thermal power plant under full operating conditions," Energy, Elsevier, vol. 185(C), pages 744-762.
    5. Liu, Ji-Zhen & Yan, Shu & Zeng, De-Liang & Hu, Yong & Lv, You, 2015. "A dynamic model used for controller design of a coal fired once-through boiler-turbine unit," Energy, Elsevier, vol. 93(P2), pages 2069-2078.
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    2. Yongmao Xiao & Jincheng Zhou & Xiaoyong Zhu & Fajun Yu, 2022. "Research on Optimization Method and Algorithm Design of Green Simultaneous Pick-up and Delivery Vehicle Scheduling under Uncertain Demand," Sustainability, MDPI, vol. 14(19), pages 1-25, October.

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