IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v126y2018icp640-651.html
   My bibliography  Save this article

Atmospheric stability and topography effects on wind turbine performance and wake properties in complex terrain

Author

Listed:
  • Han, Xingxing
  • Liu, Deyou
  • Xu, Chang
  • Shen, Wen Zhong

Abstract

This paper evaluates the influence of atmospheric stability and topography on wind turbine performance and wake properties in complex terrain. To assess atmospheric stability effects on wind turbine performance, an equivalent wind speed calculated with the power output and the manufacture power curve is proposed and calibrated with the mast hub-height wind speed. After estimating the thrust coefficient and turbulence dissipation, this paper examines wind turbine performance curves and wake profiles segregated by atmospheric stability. Results show that the equivalent wind speed at a given mast wind speed can increase by 2% under stable conditions and decrease by 5% under unstable conditions as compared with that under neutral conditions, yielding about 16% reductions of power output and thrust coefficient from stable conditions to unstable conditions. Due to the lower thrust coefficient and the enhanced turbulence, the wind turbine wakes are found to recover faster under unstable conditions than under other stability conditions. Differences in wind turbine performance and asymmetric wake profiles due to topographic effects are also observed. Results suggest that atmospheric stability and topography have significant influences on wind turbine performance and wake properties. Considering effects of atmospheric stability and topography will benefit the wind resource assessment in complex terrain.

Suggested Citation

  • Han, Xingxing & Liu, Deyou & Xu, Chang & Shen, Wen Zhong, 2018. "Atmospheric stability and topography effects on wind turbine performance and wake properties in complex terrain," Renewable Energy, Elsevier, vol. 126(C), pages 640-651.
    • Handle: RePEc:eee:renene:v:126:y:2018:i:c:p:640-651
    DOI: 10.1016/j.renene.2018.03.048
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148118303598
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.03.048?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peña, Alfredo & Réthoré, Pierre-Elouan & Rathmann, Ole, 2014. "Modeling large offshore wind farms under different atmospheric stability regimes with the Park wake model," Renewable Energy, Elsevier, vol. 70(C), pages 164-171.
    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. 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.
    2. Christy Pérez & Michel Rivero & Mauricio Escalante & Victor Ramirez & Damien Guilbert, 2023. "Influence of Atmospheric Stability on Wind Turbine Energy Production: A Case Study of the Coastal Region of Yucatan," Energies, MDPI, vol. 16(10), pages 1-20, May.
    3. 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).
    4. Xingxing Han & Tongguang Wang & Xiandong Ma & Chang Xu & Shifeng Fu & Jinmeng Zhang & Feifei Xue & Zhe Cheng, 2024. "A Nonlinear Wind Turbine Wake Expansion Model Considering Atmospheric Stability and Ground Effects," Energies, MDPI, vol. 17(17), pages 1-24, September.
    5. Antonini, Enrico G.A. & Caldeira, Ken, 2021. "Atmospheric pressure gradients and Coriolis forces provide geophysical limits to power density of large wind farms," Applied Energy, Elsevier, vol. 281(C).
    6. Dimitris Drikakis & Talib Dbouk, 2022. "The Role of Computational Science in Wind and Solar Energy: A Critical Review," Energies, MDPI, vol. 15(24), pages 1-20, December.
    7. Pacheco de Sá Sarmiento, Franciene Izis & Goes Oliveira, Jorge Luiz & Passos, Júlio César, 2022. "Impact of atmospheric stability, wake effect and topography on power production at complex-terrain wind farm," Energy, Elsevier, vol. 239(PC).
    8. Arkaitz Rabanal & Alain Ulazia & Gabriel Ibarra-Berastegi & Jon Sáenz & Unai Elosegui, 2018. "MIDAS: A Benchmarking Multi-Criteria Method for the Identification of Defective Anemometers in Wind Farms," Energies, MDPI, vol. 12(1), pages 1-19, December.
    9. Han, Xingxing & Liu, Deyou & Xu, Chang & Shen, Wen Zhong, 2020. "Similarity functions and a new k−ε closure for predicting stratified atmospheric surface layer flows in complex terrain," Renewable Energy, Elsevier, vol. 150(C), pages 907-917.
    10. Jin, Jingxin & Li, Yilin & Ye, Lin & Xu, Xunjian & Lu, Jiazheng, 2023. "Integration of atmospheric stability in wind resource assessment through multi-scale coupling method," Applied Energy, Elsevier, vol. 348(C).
    11. 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.
    12. Feng, Dachuan & Li, Larry K.B. & Gupta, Vikrant & Wan, Minping, 2022. "Componentwise influence of upstream turbulence on the far-wake dynamics of wind turbines," Renewable Energy, Elsevier, vol. 200(C), pages 1081-1091.
    13. Dar, Arslan Salim & Porté-Agel, Fernando, 2022. "Wind turbine wakes on escarpments: A wind-tunnel study," Renewable Energy, Elsevier, vol. 181(C), pages 1258-1275.
    14. Han, Qinkai & Chu, Fulei, 2021. "Directional wind energy assessment of China based on nonparametric copula models," Renewable Energy, Elsevier, vol. 164(C), pages 1334-1349.
    15. Radünz, William Corrêa & Sakagami, Yoshiaki & Haas, Reinaldo & Petry, Adriane Prisco & Passos, Júlio César & Miqueletti, Mayara & Dias, Eduardo, 2021. "Influence of atmospheric stability on wind farm performance in complex terrain," Applied Energy, Elsevier, vol. 282(PA).

    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. 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.
    2. Ohba, Masamichi & Kadokura, Shinji & Nohara, Daisuke, 2016. "Impacts of synoptic circulation patterns on wind power ramp events in East Japan," Renewable Energy, Elsevier, vol. 96(PA), pages 591-602.
    3. 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).
    4. Kevin Ray Español Lucas & Tomonori Sato & Masamichi Ohba, 2021. "Hourly Variation of Wind Speeds in the Philippines and Its Potential Impact on the Stability of the Power System," Energies, MDPI, vol. 14(8), pages 1-14, April.
    5. Cranmer, Alexana & Baker, Erin & Liesiö, Juuso & Salo, Ahti, 2018. "A portfolio model for siting offshore wind farms with economic and environmental objectives," European Journal of Operational Research, Elsevier, vol. 267(1), pages 304-314.
    6. Masoudi, Seiied Mohsen & Baneshi, Mehdi, 2022. "Layout optimization of a wind farm considering grids of various resolutions, wake effect, and realistic wind speed and wind direction data: A techno-economic assessment," Energy, Elsevier, vol. 244(PB).
    7. Astariz, S. & Perez-Collazo, C. & Abanades, J. & Iglesias, G., 2015. "Towards the optimal design of a co-located wind-wave farm," Energy, Elsevier, vol. 84(C), pages 15-24.

    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:eee:renene:v:126:y:2018:i:c:p:640-651. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.