IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i8p2722-d789165.html
   My bibliography  Save this article

A Group-Based Droop Control Strategy Considering Pitch Angle Protection to Deloaded Wind Farms

Author

Listed:
  • Hui Liu

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China
    Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Peng Wang

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China
    Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Teyang Zhao

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China
    Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Zhenggang Fan

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China
    Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Houlin Pan

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China
    Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

Abstract

To promote the frequency stability of a system with high penetration of wind power integrated into it, this paper presents a systematic frequency regulation strategy for wind farms (WFs). As preparation for frequency response, a coordinated deloading control (CDC) scheme combining the over-speed control (OSC) and the pitch angle control (PAC) methods is proposed for wind turbine generators (WTGs) to preserve power reserve. The novelty lies in the consideration of high wind speed situations and pitch angle protection. Then, a group-based droop control (GBDC) scheme is proposed for a WF consisting of WTGs with the CDC. In this scheme, WTGs are divided into two groups for different controls. To improve the frequency response performance and ensure stable operation, the droop coefficients of the WF, groups, and all WTGs are determined according to their frequency regulation capabilities (FRCs). Moreover, pitch angle protection during the frequency response process is considered in this scheme. The effectiveness of the GBDC scheme is verified by comparing it with several existing droop control schemes in various situations.

Suggested Citation

  • Hui Liu & Peng Wang & Teyang Zhao & Zhenggang Fan & Houlin Pan, 2022. "A Group-Based Droop Control Strategy Considering Pitch Angle Protection to Deloaded Wind Farms," Energies, MDPI, vol. 15(8), pages 1-23, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2722-:d:789165
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/8/2722/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/8/2722/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    2. Abraham, Aliza & Hong, Jiarong, 2020. "Dynamic wake modulation induced by utility-scale wind turbine operation," Applied Energy, Elsevier, vol. 257(C).
    3. Li, Yujun & Xu, Zhao & Zhang, Jianliang & Wong, Kit Po, 2018. "Variable gain control scheme of DFIG-based wind farm for over-frequency support," Renewable Energy, Elsevier, vol. 120(C), pages 379-391.
    4. Ochoa, Danny & Martinez, Sergio, 2018. "Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation," Renewable Energy, Elsevier, vol. 128(PA), pages 108-124.
    5. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    6. Bo Xu & Linwei Zhang & Yin Yao & Xiangdong Yu & Yixin Yang & Dongdong Li, 2021. "Virtual Inertia Coordinated Allocation Method Considering Inertia Demand and Wind Turbine Inertia Response Capability," Energies, MDPI, vol. 14(16), pages 1-15, August.
    7. Hu, Lu & Xue, Fei & Qin, Zijian & Shi, Jiying & Qiao, Wen & Yang, Wenjing & Yang, Ting, 2019. "Sliding mode extremum seeking control based on improved invasive weed optimization for MPPT in wind energy conversion system," Applied Energy, Elsevier, vol. 248(C), pages 567-575.
    8. Gao, Xiaoxia & Wang, Tengyuan & Li, Bingbing & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Zhao, Fei, 2019. "Investigation of wind turbine performance coupling wake and topography effects based on LiDAR measurements and SCADA data," Applied Energy, Elsevier, vol. 255(C).
    9. Hafiz, Faizal & Abdennour, Adel, 2015. "Optimal use of kinetic energy for the inertial support from variable speed wind turbines," Renewable Energy, Elsevier, vol. 80(C), pages 629-643.
    10. Pablo Fernández-Bustamante & Oscar Barambones & Isidro Calvo & Cristian Napole & Mohamed Derbeli, 2021. "Provision of Frequency Response from Wind Farms: A Review," Energies, MDPI, vol. 14(20), pages 1-24, 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. Matheus Schramm Dall’Asta & Telles Brunelli Lazzarin, 2024. "A Review of Fast Power-Reserve Control Techniques in Grid-Connected Wind Energy Conversion Systems," Energies, MDPI, vol. 17(2), pages 1-29, January.
    2. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    3. Wang, Huaizhi & Liu, Yangyang & Zhou, Bin & Voropai, Nikolai & Cao, Guangzhong & Jia, Youwei & Barakhtenko, Evgeny, 2020. "Advanced adaptive frequency support scheme for DFIG under cyber uncertainty," Renewable Energy, Elsevier, vol. 161(C), pages 98-109.
    4. Ana Fernández-Guillamón & Antonio Vigueras-Rodríguez & Emilio Gómez-Lázaro & Ángel Molina-García, 2018. "Fast Power Reserve Emulation Strategy for VSWT Supporting Frequency Control in Multi-Area Power Systems," Energies, MDPI, vol. 11(10), pages 1-20, October.
    5. Ting-Hsuan Chien & Yu-Chuan Huang & Yuan-Yih Hsu, 2020. "Neural Network-Based Supplementary Frequency Controller for a DFIG Wind Farm," Energies, MDPI, vol. 13(20), pages 1-15, October.
    6. Zouheyr, Dekali & Lotfi, Baghli & Abdelmadjid, Boumediene, 2021. "Improved hardware implementation of a TSR based MPPT algorithm for a low cost connected wind turbine emulator under unbalanced wind speeds," Energy, Elsevier, vol. 232(C).
    7. Kheshti, Mostafa & Ding, Lei & Nayeripour, Majid & Wang, Xiaowei & Terzija, Vladimir, 2019. "Active power support of wind turbines for grid frequency events using a reliable power reference scheme," Renewable Energy, Elsevier, vol. 139(C), pages 1241-1254.
    8. Yao, Ganzhou & Luo, Zirong & Lu, Zhongyue & Wang, Mangkuan & Shang, Jianzhong & Guerrerob, Josep M., 2023. "Unlocking the potential of wave energy conversion: A comprehensive evaluation of advanced maximum power point tracking techniques and hybrid strategies for sustainable energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    9. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    10. Fernández-Guillamón, Ana & Gómez-Lázaro, Emilio & Muljadi, Eduard & Molina-García, Ángel, 2019. "Power systems with high renewable energy sources: A review of inertia and frequency control strategies over time," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    11. Zhu, Xiaoxun & Liu, Ruizhang & Chen, Yao & Gao, Xiaoxia & Wang, Yu & Xu, Zixu, 2021. "Wind speed behaviors feather analysis and its utilization on wind speed prediction using 3D-CNN," Energy, Elsevier, vol. 236(C).
    12. Abdullah Al-Shereiqi & Amer Al-Hinai & Mohammed Albadi & Rashid Al-Abri, 2021. "Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation," Energies, MDPI, vol. 14(17), pages 1-16, August.
    13. Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2020. "A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    14. Azizi, Askar & Nourisola, Hamid & Shoja-Majidabad, Sajjad, 2019. "Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller," Renewable Energy, Elsevier, vol. 135(C), pages 55-65.
    15. Jose Rueda Torres & Zameer Ahmad & Nidarshan Veera Kumar & Elyas Rakhshani & Ebrahim Adabi & Peter Palensky & Mart van der Meijden, 2021. "Power Hardware-in-the-Loop-Based Performance Analysis of Different Converter Controllers for Fast Active Power Regulation in Low-Inertia Power Systems," Energies, MDPI, vol. 14(11), pages 1-15, June.
    16. Tavakol Aghaei, Vahid & Ağababaoğlu, Arda & Bawo, Biram & Naseradinmousavi, Peiman & Yıldırım, Sinan & Yeşilyurt, Serhat & Onat, Ahmet, 2023. "Energy optimization of wind turbines via a neural control policy based on reinforcement learning Markov chain Monte Carlo algorithm," Applied Energy, Elsevier, vol. 341(C).
    17. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    18. Pablo Fernández-Bustamante & Oscar Barambones & Isidro Calvo & Cristian Napole & Mohamed Derbeli, 2021. "Provision of Frequency Response from Wind Farms: A Review," Energies, MDPI, vol. 14(20), pages 1-24, October.
    19. Tai Li & Yanbo Wang & Sunan Sun & Huimin Qian & Leqiu Wang & Lei Wang & Yanxia Shen & Zhicheng Ji, 2023. "Fuzzy Active Disturbance Rejection-Based Virtual Inertia Control Strategy for Wind Farms," Energies, MDPI, vol. 16(10), pages 1-16, May.
    20. Xiang Li & Jing Qian & Danning Tian & Yun Zeng & Fei Cao & Lisheng Li & Ganyuan Zhang, 2023. "Maximum Power Tracking Control of Wind Turbines Based on a New Prescribed Performance Function," Energies, MDPI, vol. 16(10), pages 1-21, May.

    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:15:y:2022:i:8:p:2722-:d:789165. 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.