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Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes

Author

Listed:
  • Rogier Floors

    (DTU Wind Energy, Technical University of Denmark, Risø Campus, 4000 Roskilde, Denmark)

  • Morten Nielsen

    (DTU Wind Energy, Technical University of Denmark, Risø Campus, 4000 Roskilde, Denmark)

Abstract

A method to estimate air density as a function of elevation for wind energy resource assessments is presented. The current practice of using nearby measurements of pressure and temperature is compared with a method that uses re-analysis data. It is found that using re-analysis data to estimate air density gives similar or smaller mean absolute errors compared to using measurements that were on average located 40 km away. A method to interpolate power curves that are valid for different air densities is presented. The new model is implemented in the industry-standard model for wind resource assessment and compared with the current version of that model and shown to lead to more accurate assessment of the air density at different elevations.

Suggested Citation

  • Rogier Floors & Morten Nielsen, 2019. "Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes," Energies, MDPI, vol. 12(11), pages 1-12, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2038-:d:234858
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    Citations

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    Cited by:

    1. Mary, Asare-Addo, 2021. "Geospatial mapping of micro-wind energy for district electrification in Ghana," Energy, Elsevier, vol. 225(C).
    2. Gil Ruiz, Samuel Andrés & Barriga, Julio Eduardo Cañón & Martínez, J. Alejandro, 2021. "Wind power assessment in the Caribbean region of Colombia, using ten-minute wind observations and ERA5 data," Renewable Energy, Elsevier, vol. 172(C), pages 158-176.
    3. Gil Ruiz, Samuel Andrés & Cañón Barriga, Julio Eduardo & Martínez, J. Alejandro, 2022. "Assessment and validation of wind power potential at convection-permitting resolution for the Caribbean region of Colombia," Energy, Elsevier, vol. 244(PB).
    4. Teklebrhan Negash & Erik Möllerström & Fredric Ottermo, 2020. "An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea," Energies, MDPI, vol. 13(7), pages 1-12, April.
    5. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Walden, Jasper V.M. & Bähr, Martin & Glade, Anselm & Gollasch, Jens & Tran, A. Phong & Lorenz, Tom, 2023. "Nonlinear operational optimization of an industrial power-to-heat system with a high temperature heat pump, a thermal energy storage and wind energy," Applied Energy, Elsevier, vol. 344(C).
    7. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegi, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2019. "Global estimations of wind energy potential considering seasonal air density changes," Energy, Elsevier, vol. 187(C).
    8. Giovanni Gualtieri, 2021. "Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers," Energies, MDPI, vol. 14(14), pages 1-21, July.
    9. Alain Ulazia & Ander Nafarrate & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia, 2019. "The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential," Energies, MDPI, vol. 12(13), pages 1-18, July.
    10. Alain Ulazia & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia & Santos J. González-Rojí, 2019. "Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula," Sustainability, MDPI, vol. 11(13), pages 1-22, July.

    More about this item

    Keywords

    air density; wind energy; power curves; WAsP; ERA5; CFSR;
    All these keywords.

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