IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i5p1207-d329069.html
   My bibliography  Save this article

Linear Active Disturbance Rejection Control for DC Bus Voltage Under Low-Voltage Ride-Through at the Grid-Side of Energy Storage System

Author

Listed:
  • Youjie Ma

    (Tianjin Key Laboratory for Control Theory and Application in Complicated Systems, Tianjin University of Technology, Tianjin 300384, China)

  • Luyong Yang

    (School of Electrical and Electronic Engineering, Tianjin University of Technology, No. 391 Binshui West Road, Xiqing District, Tianjin 300384, China)

  • Xuesong Zhou

    (Tianjin Key Laboratory for Control Theory and Application in Complicated Systems, Tianjin University of Technology, Tianjin 300384, China)

  • Xia Yang

    (School of Electrical and Electronic Engineering, Tianjin University of Technology, No. 391 Binshui West Road, Xiqing District, Tianjin 300384, China)

  • Yongliang Zhou

    (School of Electrical and Electronic Engineering, Tianjin University of Technology, No. 391 Binshui West Road, Xiqing District, Tianjin 300384, China)

  • Bo Zhang

    (School of Electrical and Electronic Engineering, Tianjin University of Technology, No. 391 Binshui West Road, Xiqing District, Tianjin 300384, China)

Abstract

The energy storage inverter system has the characteristics of nonlinearity, strong coupling, variable parameters, and flexible mode switching between parallel and off grid. In order to improve the control performance of the grid-side inverter of the energy storage system, an improved Linear Active Disturbance Rejection Control (LADRC) based on proportional differentiation is proposed to replace the traditional LADRC in the voltage outer loop control. In this paper, the observation gain coefficient of the sum of the disturbances of the traditional Linear Extended State Observer (LESO) is improved to a proportional differentiation link, which effectively reduces the degree of the disturbance observation amplitude drop and the phase lag, and increases the observation bandwidth of LESO. Compared with traditional LADRC, it not only improves the observation accuracy of LESO for disturbance, but also improves the anti-interference performance of LADRC. Finally, the control effects of improved LADRC and traditional LADRC on low-voltage ride-through at different degrees are analyzed and compared through simulation, which proves the rationality of the controller designed in this paper.

Suggested Citation

  • Youjie Ma & Luyong Yang & Xuesong Zhou & Xia Yang & Yongliang Zhou & Bo Zhang, 2020. "Linear Active Disturbance Rejection Control for DC Bus Voltage Under Low-Voltage Ride-Through at the Grid-Side of Energy Storage System," Energies, MDPI, vol. 13(5), pages 1-22, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1207-:d:329069
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/5/1207/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/5/1207/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tan Yanghong & Zhang Haixia & Zhou Ye, 2018. "A Simple-to-Implement Fault Diagnosis Method for Open Switch Fault in Wind System PMSG Drives without Threshold Setting," Energies, MDPI, vol. 11(10), pages 1-18, September.
    2. Pedro G. Lind & Luis Vera-Tudela & Matthias Wächter & Martin Kühn & Joachim Peinke, 2017. "Normal Behaviour Models for Wind Turbine Vibrations: Comparison of Neural Networks and a Stochastic Approach," Energies, MDPI, vol. 10(12), pages 1-14, November.
    3. Neeraj Priyadarshi & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Farooque Azam, 2019. "An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter," Energies, MDPI, vol. 12(1), pages 1-23, January.
    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. Hemant Ahuja & Arika Singh & Sachin Sharma & Gulshan Sharma & Pitshou N. Bokoro, 2022. "Coordinated Control of Wind Energy Conversion System during Unsymmetrical Fault at Grid," Energies, MDPI, vol. 15(13), pages 1-15, July.
    2. Changsheng Yuan & Xuesong Zhou & Youjie Ma & Zhiqiang Gao & Yongliang Zhou & Chenglong Wang, 2020. "Improved Application of Third-Order LADRC in Wind Power Inverter," Energies, MDPI, vol. 13(17), pages 1-22, August.

    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. Youjie Ma & Long Tao & Xuesong Zhou & Wei Li & Xueqi Shi, 2019. "Analysis and Control of Wind Power Grid Integration Based on a Permanent Magnet Synchronous Generator Using a Fuzzy Logic System with Linear Extended State Observer," Energies, MDPI, vol. 12(15), pages 1-19, July.
    2. Youjie Ma & Faqing Zhao & Xuesong Zhou & Mao Liu & Bao Yang, 2019. "DC Side Bus Voltage Control of Wind Power Grid-Connected Inverter Based on Second-Order Linear Active Disturbance Rejection Control," Energies, MDPI, vol. 12(22), pages 1-20, November.
    3. Changsheng Yuan & Xuesong Zhou & Youjie Ma & Zhiqiang Gao & Yongliang Zhou & Chenglong Wang, 2020. "Improved Application of Third-Order LADRC in Wind Power Inverter," Energies, MDPI, vol. 13(17), pages 1-22, August.
    4. Liang Wu & Lin Guan & Feng Li & Qi Zhao & Yingjun Zhuo & Peng Chen & Yaotang Lv, 2018. "Optimal Dynamic Reactive Power Reserve for Wind Farms Addressing Short-Term Voltage Issues Caused by Wind Turbines Tripping," Energies, MDPI, vol. 11(7), pages 1-15, July.
    5. Nejra Beganovic & Jackson G. Njiri & Dirk Söffker, 2018. "Reduction of Structural Loads in Wind Turbines Based on an Adapted Control Strategy Concerning Online Fatigue Damage Evaluation Models," Energies, MDPI, vol. 11(12), pages 1-15, December.
    6. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
    7. Huang, Yuqing & Lan, Hai & Hong, Ying-Yi & Wen, Shuli & Yin, He, 2019. "Optimal generation scheduling for a deep-water semi-submersible drilling platform with uncertain renewable power generation and loads," Energy, Elsevier, vol. 181(C), pages 897-907.
    8. Zhicheng Lin & Song Zheng & Zhicheng Chen & Rong Zheng & Wang Zhang, 2019. "Application Research of the Parallel System Theory and the Data Engine Approach in Wind Energy Conversion System," Energies, MDPI, vol. 12(5), pages 1-20, March.
    9. Kuei-Hsiang Chao & Muhammad Nursyam Rizal, 2021. "A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions," Energies, MDPI, vol. 14(10), pages 1-17, May.
    10. Xuesong Zhou & Yongliang Zhou & Youjie Ma & Luyong Yang & Xia Yang & Bo Zhang, 2020. "DC Bus Voltage Control of Grid-Side Converter in Permanent Magnet Synchronous Generator Based on Improved Second-Order Linear Active Disturbance Rejection Control," Energies, MDPI, vol. 13(18), pages 1-19, September.
    11. Pedro Lencastre & Anis Yazidi & Pedro G. Lind, 2024. "Modeling Wind-Speed Statistics beyond the Weibull Distribution," Energies, MDPI, vol. 17(11), pages 1-11, May.
    12. Lee, Juyong & Cho, Youngsang, 2022. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Energy, Elsevier, vol. 239(PD).
    13. Hyun Shin & Sang Heon Chae & Eel-Hwan Kim, 2021. "Unbalanced Current Reduction Method of Microgrid Based on Power Conversion System Operation," Energies, MDPI, vol. 14(13), pages 1-16, June.
    14. Akintayo Temiloluwa Abolude & Wen Zhou, 2018. "Assessment and Performance Evaluation of a Wind Turbine Power Output," Energies, MDPI, vol. 11(8), pages 1-15, August.
    15. Omar Mohamed & Ashraf Khalil, 2020. "Progress in Modeling and Control of Gas Turbine Power Generation Systems: A Survey," Energies, MDPI, vol. 13(9), pages 1-26, May.
    16. Michał Gwóźdź & Michał Krystkowiak & Łukasz Ciepliński & Ryszard Strzelecki, 2020. "A Wind Energy Conversion System Based on a Generator with Modulated Magnetic Flux," Energies, MDPI, vol. 13(12), pages 1-18, June.
    17. Whei-Min Lin & Chung-Yuen Yang & Chia-Sheng Tu & Hsi-Shan Huang & Ming-Tang Tsai, 2019. "The Optimal Energy Dispatch of Cogeneration Systems in a Liberty Market," Energies, MDPI, vol. 12(15), pages 1-15, July.
    18. Qian, Wuyong & Wang, Jue, 2020. "An improved seasonal GM(1,1) model based on the HP filter for forecasting wind power generation in China," Energy, Elsevier, vol. 209(C).
    19. Wenxin Yu & Shoudao Huang & Weihong Xiao, 2018. "Fault Diagnosis Based on an Approach Combining a Spectrogram and a Convolutional Neural Network with Application to a Wind Turbine System," Energies, MDPI, vol. 11(10), pages 1-11, September.
    20. Eltamaly, Ali M. & Al-Saud, M.S. & Abokhalil, Ahmed G. & Farh, Hassan M.H., 2020. "Simulation and experimental validation of fast adaptive particle swarm optimization strategy for photovoltaic global peak tracker under dynamic partial shading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).

    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:13:y:2020:i:5:p:1207-:d:329069. 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.