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Atmospheric pressure gradients and Coriolis forces provide geophysical limits to power density of large wind farms

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  • Antonini, Enrico G.A.
  • Caldeira, Ken

Abstract

The geophysical limit to maximum land-area power density of large wind farms is related to the rate of replenishment of kinetic energy removed from the atmosphere by wind turbines. Although observations and numerical simulations have indicated an upper bound to the power density in the order of 1 W/m2, no theoretical foundation has yet been provided. Here, we study the role of atmospheric pressure gradients and the latitude-dependent Coriolis parameter in the power density of large-scale wind farms by means of both numerical atmospheric simulations and analytic expressions. We illustrate that energy transport to regional-scale wind farms is primarily governed by horizontal pressure gradients and their interaction with the Coriolis force and turbine-induced surface drag within the latitude-dependent Ekman layer. Higher pressure gradients and lower Coriolis parameters promote higher energy availability and, consequently, higher potential power density, suggesting that the power density of regional-scale wind farms is largely resource- and location-dependent.

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  • 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).
    • Handle: RePEc:eee:appene:v:281:y:2021:i:c:s0306261920314835
    DOI: 10.1016/j.apenergy.2020.116048
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    References listed on IDEAS

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    1. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2018. "Continuous adjoint formulation for wind farm layout optimization: A 2D implementation," Applied Energy, Elsevier, vol. 228(C), pages 2333-2345.
    2. Lewis, Joanna I. & Wiser, Ryan H., 2007. "Fostering a renewable energy technology industry: An international comparison of wind industry policy support mechanisms," Energy Policy, Elsevier, vol. 35(3), pages 1844-1857, March.
    3. Pope, K. & Dincer, I. & Naterer, G.F., 2010. "Energy and exergy efficiency comparison of horizontal and vertical axis wind turbines," Renewable Energy, Elsevier, vol. 35(9), pages 2102-2113.
    4. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2019. "Improving CFD wind farm simulations incorporating wind direction uncertainty," Renewable Energy, Elsevier, vol. 133(C), pages 1011-1023.
    5. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
    6. 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.
    7. Krohn, Søren & Damborg, Steffen, 1999. "On public attitudes towards wind power," Renewable Energy, Elsevier, vol. 16(1), pages 954-960.
    8. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2020. "Optimal design of wind farms in complex terrains using computational fluid dynamics and adjoint methods," Applied Energy, Elsevier, vol. 261(C).
    9. Leah C. Stokes & Christopher Warshaw, 2017. "Renewable energy policy design and framing influence public support in the United States," Nature Energy, Nature, vol. 2(8), pages 1-6, August.
    10. Kate Marvel & Ben Kravitz & Ken Caldeira, 2013. "Geophysical limits to global wind power," Nature Climate Change, Nature, vol. 3(2), pages 118-121, February.
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    Cited by:

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