IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v325y2022ics0306261922011758.html
   My bibliography  Save this article

Robust regulation for superheated steam temperature control based on data-driven feedback compensation

Author

Listed:
  • Li, Xiaoming
  • Yu, Xinghuo

Abstract

Control of the superheated steam temperature is a significant technical challenge to coal-fired power plants due to the strong nonlinearity, large inertia and parameter uncertainties with external disturbances. This paper proposes a robust proportion–integration–differentiation (PID) control of the superheated steam temperature with proven stability and the external disturbance rejection. The design is based on the proposed data-driven feedback compensator (DFC) which is a neural network (NN) trained to isolate the nonlinearity and inertia from the PID controller, allowing the system for tuning the PID controller can be simplified as an approximate linear system with the modeling error based-feedback and feed-forward compensations. Then, the PID controller is tuned by the Nyquist stability criterion to place every closed-loop pole to a specific region in the left-half s-plane to guarantee the stability with considering the modeling error. Besides, a NN based feed-forward compensator is trained as the inverse model of the feedback compensator to further smooth the temperature fluctuation caused by the disturbance. The simulations and engineering implementation of the superheated steam temperature controls for a coal-fired power plant in Australia show the effectiveness.

Suggested Citation

  • Li, Xiaoming & Yu, Xinghuo, 2022. "Robust regulation for superheated steam temperature control based on data-driven feedback compensation," Applied Energy, Elsevier, vol. 325(C).
  • Handle: RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011758
    DOI: 10.1016/j.apenergy.2022.119918
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922011758
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.119918?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mikulandrić, Robert & Lončar, Dražen & Cvetinović, Dejan & Spiridon, Gabriel, 2013. "Improvement of existing coal fired thermal power plants performance by control systems modifications," Energy, Elsevier, vol. 57(C), pages 55-65.
    2. Zhao, Zhigang & Su, Sheng & Si, Ningning & Hu, Song & Wang, Yi & Xu, Jun & Jiang, Long & Chen, Gang & Xiang, Jun, 2017. "Exergy analysis of the turbine system in a 1000 MW double reheat ultra-supercritical power plant," Energy, Elsevier, vol. 119(C), pages 540-548.
    3. Wang, Chaoyang & Qiao, Yongqiang & Liu, Ming & Zhao, Yongliang & Yan, Junjie, 2020. "Enhancing peak shaving capability by optimizing reheat-steam temperature control of a double-reheat boiler," Applied Energy, Elsevier, vol. 260(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaobo Cui & Pan Xu & Guohui Song & Haiming Gu & Hui Gu & Liang Wang & Hongxia Zhu, 2022. "PID Control of a Superheated Steam Temperature System Based on Integral Gain Scheduling," Energies, MDPI, vol. 15(23), pages 1-16, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Shunqi & Liu, Ming & Ma, Yuegeng & Liu, Jiping & Yan, Junjie, 2021. "Flexibility assessment of a modified double-reheat Rankine cycle integrating a regenerative turbine during recuperative heater shutdown processes," Energy, Elsevier, vol. 233(C).
    2. Wang, Zhu & Liu, Ming & Yan, Junjie, 2021. "Flexibility and efficiency co-enhancement of thermal power plant by control strategy improvement considering time varying and detailed boiler heat storage characteristics," Energy, Elsevier, vol. 232(C).
    3. Yu, Jianxi & Liu, Pei & Li, Zheng, 2021. "Data reconciliation of the thermal system of a double reheat power plant for thermal calculation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    4. Opriș, Ioana & Cenușă, Victor-Eduard, 2023. "Parametric and heuristic optimization of multiple schemes with double-reheat ultra-supercritical steam power plants," Energy, Elsevier, vol. 266(C).
    5. Kravanja, Gregor & Zajc, Gašper & Knez, Željko & Škerget, Mojca & Marčič, Simon & Knez, Maša H., 2018. "Heat transfer performance of CO2, ethane and their azeotropic mixture under supercritical conditions," Energy, Elsevier, vol. 152(C), pages 190-201.
    6. Zhou, Jing & Zhu, Meng & Su, Sheng & Chen, Lei & Xu, Jun & Hu, Song & Wang, Yi & Jiang, Long & Zhong, Wenqi & Xiang, Jun, 2020. "Numerical analysis and modified thermodynamic calculation methods for the furnace in the 1000 MW supercritical CO2 coal-fired boiler," Energy, Elsevier, vol. 212(C).
    7. Waqar Muhammad Ashraf & Ghulam Moeen Uddin & Syed Muhammad Arafat & Sher Afghan & Ahmad Hassan Kamal & Muhammad Asim & Muhammad Haider Khan & Muhammad Waqas Rafique & Uwe Naumann & Sajawal Gul Niazi &, 2020. "Optimization of a 660 MW e Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management Part 1. Thermal Efficiency," Energies, MDPI, vol. 13(21), pages 1-33, October.
    8. Braimakis, Konstantinos & Magiri-Skouloudi, Despina & Grimekis, Dimitrios & Karellas, Sotirios, 2020. "Εnergy-exergy analysis of ultra-supercritical biomass-fuelled steam power plants for industrial CHP, district heating and cooling," Renewable Energy, Elsevier, vol. 154(C), pages 252-269.
    9. Yan, Hui & Liu, Ming & Wang, Zhu & Zhang, Kezhen & Chong, Daotong & Yan, Junjie, 2023. "Flexibility enhancement of solar-aided coal-fired power plant under different direct normal irradiance conditions," Energy, Elsevier, vol. 262(PA).
    10. Wang, Zhu & Liu, Ming & Zhao, Yongliang & Wang, Chaoyang & Chong, Daotong & Yan, Junjie, 2020. "Flexibility and efficiency enhancement for double-reheat coal-fired power plants by control optimization considering boiler heat storage," Energy, Elsevier, vol. 201(C).
    11. Yu, Jianxi & Petersen, Nils & Liu, Pei & Li, Zheng & Wirsum, Manfred, 2022. "Hybrid modelling and simulation of thermal systems of in-service power plants for digital twin development," Energy, Elsevier, vol. 260(C).
    12. Ouyang, Tiancheng & Xu, Jisong & Qin, Peijia & Cheng, Liang, 2022. "Utilizing flue gas low-grade waste heat and furnace excess heat to produce syngas and sulfuric acid recovery in coal-fired power plant," Energy, Elsevier, vol. 258(C).
    13. Taler, Jan & Trojan, Marcin & Dzierwa, Piotr & Kaczmarski, Karol & Węglowski, Bohdan & Taler, Dawid & Zima, Wiesław & Grądziel, Sławomir & Ocłoń, Paweł & Sobota, Tomasz & Rerak, Monika & Jaremkiewicz,, 2023. "The flexible boiler operation in a wide range of load changes with considering the strength and environmental restrictions," Energy, Elsevier, vol. 263(PB).
    14. Abubaker, Ahmad M. & Darwish Ahmad, Adnan & Salaimeh, Ahmad A. & Akafuah, Nelson K. & Saito, Kozo, 2022. "A novel solar combined cycle integration: An exergy-based optimization using artificial neural network," Renewable Energy, Elsevier, vol. 181(C), pages 914-932.
    15. Hou, Guolian & Gong, Linjuan & Hu, Bo & Huang, Ting & Su, Huilin & Huang, Congzhi & Zhou, Guiping & Wang, Shunjiang, 2022. "Flexibility oriented adaptive modeling of combined heat and power plant under various heat-power coupling conditions," Energy, Elsevier, vol. 242(C).
    16. Zhou, Jing & Zhu, Meng & Xu, Kai & Su, Sheng & Tang, Yifang & Hu, Song & Wang, Yi & Xu, Jun & He, Limo & Xiang, Jun, 2020. "Key issues and innovative double-tangential circular boiler configurations for the 1000 MW coal-fired supercritical carbon dioxide power plant," Energy, Elsevier, vol. 199(C).
    17. Wang, Chaoyang & Qiao, Yongqiang & Liu, Ming & Zhao, Yongliang & Yan, Junjie, 2020. "Enhancing peak shaving capability by optimizing reheat-steam temperature control of a double-reheat boiler," Applied Energy, Elsevier, vol. 260(C).
    18. Yu, Jianxi & Han, Wenquan & Chen, Kang & Liu, Pei & Li, Zheng, 2022. "Gross error detection in steam turbine measurements based on data reconciliation of inequality constraints," Energy, Elsevier, vol. 253(C).
    19. Sha Liu & Jiong Shen, 2022. "Modeling of Large-Scale Thermal Power Plants for Performance Prediction in Deep Peak Shaving," Energies, MDPI, vol. 15(9), pages 1-18, April.
    20. Wang, Yanhong & Cao, Lihua & Hu, Pengfei & Li, Bo & Li, Yong, 2019. "Model establishment and performance evaluation of a modified regenerative system for a 660 MW supercritical unit running at the IPT-setting mode," Energy, Elsevier, vol. 179(C), pages 890-915.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011758. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.