IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i19p6934-d1252850.html
   My bibliography  Save this article

Dynamic Equivalent Modeling of a Large Renewable Power Plant Using a Data-Driven Degree of Similarity Method

Author

Listed:
  • Mengjun Liao

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Lin Zhu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)

  • Yonghao Hu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)

  • Yang Liu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)

  • Yue Wu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)

  • Leke Chen

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)

Abstract

This paper aims to develop a novel method for the dynamic equivalence of a renewable power plant, ultimately contributing to power system modeling and enhancing the integration of renewable energy sources. In order to address the challenge posed by clusters of renewable generation units during the equivalence process, the paper introduces the degree of similarity to assess similarity features under data. After leveraging the degree of similarity in conjunction with data-driven techniques, the proposed method efficiently entails dividing numerous units in a large-scale plant into distinct clusters. Additionally, the paper adopts practical algorithms to determine the parameters for each aggregated cluster and streamline the intricate collector network within the renewable power plant. The equivalent model of a renewable power plant is thereby conclusively derived. Comprehensive case studies are conducted within a practical offshore wind plant setting. These case studies are accompanied by simulations, highlighting the advantages and effectiveness of the proposed method, offering an accurate representation of the renewable power plant under diverse operating conditions.

Suggested Citation

  • Mengjun Liao & Lin Zhu & Yonghao Hu & Yang Liu & Yue Wu & Leke Chen, 2023. "Dynamic Equivalent Modeling of a Large Renewable Power Plant Using a Data-Driven Degree of Similarity Method," Energies, MDPI, vol. 16(19), pages 1-20, October.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6934-:d:1252850
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/19/6934/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/19/6934/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    2. Soobae Kim & Thomas J. Overbye, 2022. "Partial Y-Bus Factorization Algorithm for Power System Dynamic Equivalents," Energies, MDPI, vol. 15(3), pages 1-10, January.
    3. Ning Zhou & Huan Ma & Junchao Chen & Qiao Fang & Zhe Jiang & Changgang Li, 2023. "Equivalent Modeling of LVRT Characteristics for Centralized DFIG Wind Farms Based on PSO and DBSCAN," Energies, MDPI, vol. 16(6), pages 1-21, March.
    4. Pingping Han & Zihao Lin & Lei Wang & Guijun Fan & Xiaoan Zhang, 2018. "A Survey on Equivalence Modeling for Large-Scale Photovoltaic Power Plants," Energies, MDPI, vol. 11(6), pages 1-14, June.
    5. Yun, Eunjeong & Hur, Jin, 2021. "Probabilistic estimation model of power curve to enhance power output forecasting of wind generating resources," Energy, Elsevier, vol. 223(C).
    6. Linan Qu & Shujie Zhang & Hsiung-Cheng Lin & Ning Chen & Lingling Li, 2020. "Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method," Energies, MDPI, vol. 13(14), pages 1-15, July.
    7. Donghyeon Lee & Seungwan Son & Insu Kim, 2021. "Optimal Allocation of Large-Capacity Distributed Generation with the Volt/Var Control Capability Using Particle Swarm Optimization," Energies, MDPI, vol. 14(11), pages 1-19, May.
    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. Işık, Cem & Kuziboev, Bekhzod & Ongan, Serdar & Saidmamatov, Olimjon & Mirkhoshimova, Mokhirakhon & Rajabov, Alibek, 2024. "The volatility of global energy uncertainty: Renewable alternatives," Energy, Elsevier, vol. 297(C).
    2. Xiangwu Yan & Jiajia Li & Ling Wang & Shuaishuai Zhao & Tie Li & Zhipeng Lv & Ming Wu, 2018. "Adaptive-MPPT-Based Control of Improved Photovoltaic Virtual Synchronous Generators," Energies, MDPI, vol. 11(7), pages 1-18, July.
    3. Hu, Yusha & Man, Yi, 2023. "Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    4. Francisco Bilendo & Angela Meyer & Hamed Badihi & Ningyun Lu & Philippe Cambron & Bin Jiang, 2022. "Applications and Modeling Techniques of Wind Turbine Power Curve for Wind Farms—A Review," Energies, MDPI, vol. 16(1), pages 1-38, December.
    5. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
    6. Wang, Peng & Li, Yanting & Zhang, Guangyao, 2023. "Probabilistic power curve estimation based on meteorological factors and density LSTM," Energy, Elsevier, vol. 269(C).
    7. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Liu, Yu & Wu, Chuanshen & Wang, Sicheng, 2021. "Congestion-aware robust security constrained unit commitment model for AC-DC grids," Applied Energy, Elsevier, vol. 304(C).
    8. Christopher Jung & Dirk Schindler, 2023. "Reasons for the Recent Onshore Wind Capacity Factor Increase," Energies, MDPI, vol. 16(14), pages 1-17, July.
    9. Yu, Dong & Gao, Shan & Han, Haiteng & Zhao, Xin & Wu, Chuanshen & Liu, Yu & Song, Tiancheng E., 2024. "Intraday two-stage hierarchical optimal scheduling model for multiarea AC/DC systems with wind power integration," Applied Energy, Elsevier, vol. 364(C).
    10. Hao He & Jia Li & Weizhe Zhao & Boyang Li & Yalong Li, 2022. "Reactive Power and Voltage Optimization of New-Energy Grid Based on the Improved Flower Pollination Algorithm," Energies, MDPI, vol. 15(10), pages 1-12, May.
    11. Jaemin Park & Haesung Jo & Insu Kim, 2021. "The Selection of the Most Cost-Efficient Distributed Generation Type for a Combined Cooling Heat and Power System Used for Metropolitan Residential Customers," Energies, MDPI, vol. 14(18), pages 1-25, September.
    12. Davide Astolfi & Francesco Castellani & Andrea Lombardi & Ludovico Terzi, 2021. "Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring," Energies, MDPI, vol. 14(4), pages 1-18, February.
    13. Wang, Yun & Duan, Xiaocong & Zou, Runmin & Zhang, Fan & Li, Yifen & Hu, Qinghua, 2023. "A novel data-driven deep learning approach for wind turbine power curve modeling," Energy, Elsevier, vol. 270(C).
    14. Kai-Hung Lu & Qianlin Rao, 2023. "Enhancing the Dynamic Stability of Integrated Offshore Wind Farms and Photovoltaic Farms Using STATCOM with Intelligent Damping Controllers," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    15. Qianlong Zhu & Jun Tao & Tianbai Deng & Mingxing Zhu, 2022. "A General Equivalent Modeling Method for DFIG Wind Farms Based on Data-Driven Modeling," Energies, MDPI, vol. 15(19), pages 1-14, September.
    16. He, Wei & Xu, Qing & Liu, Shengchun & Wang, Tieying & Wang, Fang & Wu, Xiaohui & Wang, Yulin & Li, Hailong, 2024. "Analysis on data center power supply system based on multiple renewable power configurations and multi-objective optimization," Renewable Energy, Elsevier, vol. 222(C).
    17. Elyas Rakhshani & Kumars Rouzbehi & Adolfo J. Sánchez & Ana Cabrera Tobar & Edris Pouresmaeil, 2019. "Integration of Large Scale PV-Based Generation into Power Systems: A Survey," Energies, MDPI, vol. 12(8), pages 1-19, April.
    18. Peiru Feng & Jiayin Xu & Zhuang Wang & Shenghu Li & Yuming Shen & Xu Gui, 2024. "Impact of Phase Angle Jump on a Doubly Fed Induction Generator under Low-Voltage Ride-Through Based on Transfer Function Decomposition," Energies, MDPI, vol. 17(19), pages 1-17, September.
    19. Guo, Xusheng & Lou, Suhua & Chen, Zhe & Wu, Yaowu, 2022. "Flexible operation of integrated energy system with HVDC infeed considering multi-retrofitted combined heat and power units," Applied Energy, Elsevier, vol. 325(C).
    20. Junjun Zhang & Yaojie Sun & Meiyin Liu & Wei Dong & Pingping Han, 2018. "Research on Modeling of Microgrid Based on Data Testing and Parameter Identification," Energies, MDPI, vol. 11(10), pages 1-15, September.

    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:16:y:2023:i:19:p:6934-:d:1252850. 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.