IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i17p3387-d263421.html
   My bibliography  Save this article

Power Oscillation Damping from Offshore Wind Farms Connected to HVDC via Diode Rectifiers

Author

Listed:
  • Oscar Saborío-Romano

    (Department of Wind Energy, Technical University of Denmark, Building 115, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark)

  • Ali Bidadfar

    (Department of Wind Energy, Technical University of Denmark, Building 115, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark)

  • Ömer Göksu

    (Department of Wind Energy, Technical University of Denmark, Building 115, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark)

  • Lorenzo Zeni

    (rsted Offshore, Nesa Allé 1, 2820 Gentofte, Denmark)

  • Nicolaos A. Cutululis

    (Department of Wind Energy, Technical University of Denmark, Building 115, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark)

Abstract

Diode rectifiers (DRs) have elicited increasing interest from both industry and academia as a feasible alternative for connecting offshore wind farms (OWFs) to HVDC networks. However, before such technology is deployed, more studies are needed to assess the actual capabilities of DR-connected OWFs to contribute to the secure operation of the networks linked to them. This study assessed the capability of such an OWF to provide support to an onshore AC network by means of (active) power oscillation damping (POD). A semi-aggregated OWF representation was considered in order to examine the dynamics of each grid-forming wind turbine (WT) within a string when providing POD, while achieving reasonable simulation times. Simulation results corroborate that such an OWF can provide POD by means of OWF active power controls similar to those developed for OWFs connected to HVDC via voltage source converters, while its grid-forming WTs share the reactive power consumption/production and keep the offshore voltage frequency and magnitude within their normal operating ranges. Open-loop test results show that such capability can, however, be restricted at operating points corresponding to the lowest and highest values of active power output.

Suggested Citation

  • Oscar Saborío-Romano & Ali Bidadfar & Ömer Göksu & Lorenzo Zeni & Nicolaos A. Cutululis, 2019. "Power Oscillation Damping from Offshore Wind Farms Connected to HVDC via Diode Rectifiers," Energies, MDPI, vol. 12(17), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3387-:d:263421
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/17/3387/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/17/3387/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Göçmen, Tuhfe & Laan, Paul van der & Réthoré, Pierre-Elouan & Diaz, Alfredo Peña & Larsen, Gunner Chr. & Ott, Søren, 2016. "Wind turbine wake models developed at the technical university of Denmark: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 752-769.
    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. Ali Bidadfar & Oscar Saborío-Romano & Vladislav Akhmatov & Nicolaos A. Cutululis & Poul E. Sørensen, 2019. "Impact of Primary Frequency Control of Offshore HVDC Grids on Interarea Modes of Power Systems," Energies, MDPI, vol. 12(20), pages 1-14, October.

    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. Ziyu Zhang & Peng Huang & Haocheng Sun, 2020. "A Novel Analytical Wake Model with a Cosine-Shaped Velocity Deficit," Energies, MDPI, vol. 13(13), pages 1-20, June.
    2. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
    3. Yaqing Jin & Huiwen Liu & Rajan Aggarwal & Arvind Singh & Leonardo P. Chamorro, 2016. "Effects of Freestream Turbulence in a Model Wind Turbine Wake," Energies, MDPI, vol. 9(10), pages 1-12, October.
    4. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Li, Qi, 2019. "A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes," Applied Energy, Elsevier, vol. 233, pages 975-984.
    5. Li, B. & Zhou, D.L. & Wang, Y. & Shuai, Y. & Liu, Q.Z. & Cai, W.H., 2020. "The design of a small lab-scale wind turbine model with high performance similarity to its utility-scale prototype," Renewable Energy, Elsevier, vol. 149(C), pages 435-444.
    6. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    7. Jiufa Cao & Weijun Zhu & Xinbo Wu & Tongguang Wang & Haoran Xu, 2018. "An Aero-acoustic Noise Distribution Prediction Methodology for Offshore Wind Farms," Energies, MDPI, vol. 12(1), pages 1-16, December.
    8. Zehtabiyan-Rezaie, Navid & Abkar, Mahdi, 2024. "An extended k−ɛ model for wake-flow simulation of wind farms," Renewable Energy, Elsevier, vol. 222(C).
    9. Kyoungboo Yang, 2020. "Determining an Appropriate Parameter of Analytical Wake Models for Energy Capture and Layout Optimization on Wind Farms," Energies, MDPI, vol. 13(3), pages 1-17, February.
    10. Li, Xuyang & Qiu, Yingning & Feng, Yanhui & Wang, Zheng, 2021. "Wind turbine power prediction considering wake effects with dual laser beam LiDAR measured yaw misalignment," Applied Energy, Elsevier, vol. 299(C).
    11. Wu, Chutian & Yang, Xiaolei & Zhu, Yaxin, 2021. "On the design of potential turbine positions for physics-informed optimization of wind farm layout," Renewable Energy, Elsevier, vol. 164(C), pages 1108-1120.
    12. Khadijah Barashid & Amr Munshi & Ahmad Alhindi, 2023. "Wind Farm Power Prediction Considering Layout and Wake Effect: Case Study of Saudi Arabia," Energies, MDPI, vol. 16(2), pages 1-22, January.
    13. Ti, Zilong & Deng, Xiao Wei & Zhang, Mingming, 2021. "Artificial Neural Networks based wake model for power prediction of wind farm," Renewable Energy, Elsevier, vol. 172(C), pages 618-631.
    14. Yang, Shanghui & Deng, Xiaowei & Ti, Zilong & Yan, Bowen & Yang, Qingshan, 2022. "Cooperative yaw control of wind farm using a double-layer machine learning framework," Renewable Energy, Elsevier, vol. 193(C), pages 519-537.
    15. Göçmen, Tuhfe & Giebel, Gregor, 2016. "Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms," Renewable Energy, Elsevier, vol. 99(C), pages 524-532.
    16. Eidi, Ali & Ghiassi, Reza & Yang, Xiang & Abkar, Mahdi, 2021. "Model-form uncertainty quantification in RANS simulations of wakes and power losses in wind farms," Renewable Energy, Elsevier, vol. 179(C), pages 2212-2223.
    17. Huanqiang, Zhang & Xiaoxia, Gao & Hongkun, Lu & Qiansheng, Zhao & Xiaoxun, Zhu & Yu, Wang & Fei, Zhao, 2024. "Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave," Applied Energy, Elsevier, vol. 365(C).
    18. Pérez Albornoz, C. & Escalante Soberanis, M.A. & Ramírez Rivera, V. & Rivero, M., 2022. "Review of atmospheric stability estimations for wind power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    19. Dong, Xinghui & Li, Jia & Gao, Di & Zheng, Kai, 2021. "Wind speed modeling for cascade clusters of wind turbines Part 2: Wind speed reduction and aggregation superposition," Energy, Elsevier, vol. 215(PB).
    20. Amin Allah, Veisi & Shafiei Mayam, Mohammad Hossein, 2017. "Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines," Energy, Elsevier, vol. 121(C), pages 533-544.

    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:12:y:2019:i:17:p:3387-:d:263421. 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.