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Wind Farm Blockage and the Consequences of Neglecting Its Impact on Energy Production

Author

Listed:
  • James Bleeg

    (DNV GL, Group Technology & Research, Power & Renewables, Bristol BS2 0PS, UK)

  • Mark Purcell

    (DNV GL, Energy, Project Development, Melbourne 3008, Australia)

  • Renzo Ruisi

    (DNV GL, Group Technology & Research, Power & Renewables, Bristol BS2 0PS, UK
    DNV GL, Energy, Project Development, Glasgow G1 2PR, UK)

  • Elizabeth Traiger

    (DNV GL, Group Technology & Research, Power & Renewables, Bristol BS2 0PS, UK)

Abstract

Measurements taken before and after the commissioning of three wind farms reveal that the wind speeds just upstream of each wind farm decrease relative to locations farther away after the turbines are turned on. At a distance of two rotor diameters upstream, the average derived relative slowdown is 3.4%; at seven to ten rotor diameters upstream, the average slowdown is 1.9%. Reynolds-Averaged Navier-Stokes (RANS) simulations point to wind-farm-scale blockage as the primary cause of these slowdowns. Blockage effects also cause front row turbines to produce less energy than they each would operating in isolation. Wind energy prediction procedures in use today ignore this effect, resulting in an overprediction bias that pervades the entire wind farm.

Suggested Citation

  • James Bleeg & Mark Purcell & Renzo Ruisi & Elizabeth Traiger, 2018. "Wind Farm Blockage and the Consequences of Neglecting Its Impact on Energy Production," Energies, MDPI, vol. 11(6), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1609-:d:153434
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    Citations

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    Cited by:

    1. Hayat, Imran & Chatterjee, Tanmoy & Liu, Huiwen & Peet, Yulia T. & Chamorro, Leonardo P., 2019. "Exploring wind farms with alternating two- and three-bladed wind turbines," Renewable Energy, Elsevier, vol. 138(C), pages 764-774.
    2. Leila Legris & Morten Lindholt Pahus & Takafumi Nishino & Edgar Perez-Campos, 2022. "Prediction and Mitigation of Wind Farm Blockage Losses Considering Mesoscale Atmospheric Response," Energies, MDPI, vol. 16(1), pages 1-17, December.
    3. Janusz Kulejewski & Nabi Ibadov & Jerzy Rosłon & Jacek Zawistowski, 2021. "Cash Flow Optimization for Renewable Energy Construction Projects with a New Approach to Critical Chain Scheduling," Energies, MDPI, vol. 14(18), pages 1-15, September.
    4. Mihaela Popescu & Tore Flåtten, 2021. "A Study of Blockage Effects at the Wind Turbine and Wind Farm Scales," Energies, MDPI, vol. 14(19), pages 1-19, September.
    5. Kelan Patel & Thomas D. Dunstan & Takafumi Nishino, 2021. "Time-Dependent Upper Limits to the Performance of Large Wind Farms Due to Mesoscale Atmospheric Response," Energies, MDPI, vol. 14(19), pages 1-16, October.
    6. Meyer Forsting, Alexander R. & Navarro Diaz, Gonzalo P. & Segalini, Antonio & Andersen, Søren J. & Ivanell, Stefan, 2023. "On the accuracy of predicting wind-farm blockage," Renewable Energy, Elsevier, vol. 214(C), pages 114-129.
    7. Erik Möllerström & Sean Gregory & Aromal Sugathan, 2021. "Improvement of AEP Predictions with Time for Swedish Wind Farms," Energies, MDPI, vol. 14(12), pages 1-12, June.
    8. Strickland, Jessica M.I. & Gadde, Srinidhi N. & Stevens, Richard J.A.M., 2022. "Wind farm blockage in a stable atmospheric boundary layer," Renewable Energy, Elsevier, vol. 197(C), pages 50-58.
    9. Beatriz Cañadillas & Richard Foreman & Gerald Steinfeld & Nick Robinson, 2023. "Cumulative Interactions between the Global Blockage and Wake Effects as Observed by an Engineering Model and Large-Eddy Simulations," Energies, MDPI, vol. 16(7), pages 1-24, March.
    10. Steven Knoop & Pooja Ramakrishnan & Ine Wijnant, 2020. "Dutch Offshore Wind Atlas Validation against Cabauw Meteomast Wind Measurements," Energies, MDPI, vol. 13(24), pages 1-21, December.

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