IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i4p924-d1339823.html
   My bibliography  Save this article

Engineering Fastest Control: A New Process Control Method for Thermal Power Units

Author

Listed:
  • Shangyao Shi

    (School of Software, North University of China, Taiyuan 030051, China)

  • Jiayu Chen

    (School of Aerospace Engineering, North University of China, Taiyuan 030051, China)

  • Jun Li

    (Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China)

  • Jiahao Liu

    (School of Software, North University of China, Taiyuan 030051, China
    School of Mechanical Engineering, North University of China, Taiyuan 030051, China)

  • Ziyi Wang

    (School of Aerospace Engineering, North University of China, Taiyuan 030051, China)

  • Zhiru Li

    (School of Aerospace Engineering, North University of China, Taiyuan 030051, China)

  • Pengyun Chen

    (School of Software, North University of China, Taiyuan 030051, China
    School of Aerospace Engineering, North University of China, Taiyuan 030051, China)

  • Lizhou Li

    (School of Aerospace Engineering, North University of China, Taiyuan 030051, China)

Abstract

The intermittent and volatile nature of wind power generation necessitates thermal power units to provide deep-peak shaving and fast frequency regulation services within the same grid. However, the current proportional integral differential (PID) control performance in the process control foundation of thermal power units falls short of meeting these requirements. Despite the lack of comprehensive research on engineering fastest control (EFC), this article aims to address this gap by studying and analyzing the mechanism and physical defects of the fast tracking filter (FTF), the output tracking input characteristics of EFTF reconstructed by FTF engineering, and the control performance of the constructed EFC. Through mathematical calculation analysis, simulation experiments, and real-world engineering practice, it is concluded that EFC surpasses the limitations of PID control performance and effectively enhances feedback control performance. As a result, it is deemed suitable for process control in thermal power units.

Suggested Citation

  • Shangyao Shi & Jiayu Chen & Jun Li & Jiahao Liu & Ziyi Wang & Zhiru Li & Pengyun Chen & Lizhou Li, 2024. "Engineering Fastest Control: A New Process Control Method for Thermal Power Units," Energies, MDPI, vol. 17(4), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:924-:d:1339823
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/4/924/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/4/924/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yunna Wu & Chuanbo Xu & Hu Xu, 2016. "Optimal Site Selection of Tidal Power Plants Using a Novel Method: A Case in China," Energies, MDPI, vol. 9(10), pages 1-26, October.
    Full references (including those not matched with items on IDEAS)

    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. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Chen, Kaifeng & Sun, Xiaokun, 2018. "An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China," Energy, Elsevier, vol. 143(C), pages 295-309.
    2. Mayke Feitosa Progênio & Claudio José Cavalcante Blanco & Josias Silva Cruz & Felipe Antônio Melo Costa Filho & André Luiz Amarante Mesquita, 2021. "Environmental impact index for tidal power plants in amazon region coast," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10814-10830, July.
    3. Yang, Zhixue & Ren, Zhouyang & Li, Hui & Pan, Zhen & Xia, Weiyi, 2024. "A review of tidal current power generation farm planning: Methodologies, characteristics and challenges," Renewable Energy, Elsevier, vol. 220(C).
    4. Lihui Zhang & He Xin & Zhinan Kan, 2019. "Sustainability Performance Evaluation of Hybrid Energy System Using an Improved Fuzzy Synthetic Evaluation Approach," Sustainability, MDPI, vol. 11(5), pages 1-19, February.

    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:gam:jeners:v:17:y:2024:i:4:p:924-:d:1339823. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.