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Global estimations of wind energy potential considering seasonal air density changes

Author

Listed:
  • Ulazia, Alain
  • Sáenz, Jon
  • Ibarra-Berastegi, Gabriel
  • González-Rojí, Santos J.
  • Carreno-Madinabeitia, Sheila

Abstract

The literature typically considers constant annual average air density when computing the wind energy potential of a given location. In this work, the recent reanalysis ERA5 is used to obtain global seasonal estimates of wind energy production that include seasonally varying air density. Thus, errors due to the use of a constant air density are quantified. First, seasonal air density changes are studied at the global scale. Then, wind power density errors due to seasonal air density changes are computed. Finally, winter and summer energy production errors due to neglecting the changes in air density are computed by implementing the power curve of the National Renewable Energy Laboratorys 5 MW turbine. Results show relevant deviations for three variables (air density, wind power density, and energy production), mainly in the middle-high latitudes (Hudson Bay, Siberia, Patagonia, Australia, etc.). Locations with variations from −6% to 6% are identified from summers to winters in the Northern Hemisphere. Additionally, simulations with the aeroelastic code FAST for the studied turbine show that instantaneous power production can be affected by greater than 20% below the rated wind speed if a day with realistically high or low air density values is compared for the same turbulent wind speed.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219316226
    DOI: 10.1016/j.energy.2019.115938
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    1. Dvorak, Michael J. & Archer, Cristina L. & Jacobson, Mark Z., 2010. "California offshore wind energy potential," Renewable Energy, Elsevier, vol. 35(6), pages 1244-1254.
    2. Carvalho, D. & Rocha, A. & Santos, C. Silva & Pereira, R., 2013. "Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques," Applied Energy, Elsevier, vol. 108(C), pages 493-504.
    3. Ramirez Camargo, Luis & Gruber, Katharina & Nitsch, Felix, 2019. "Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems," Renewable Energy, Elsevier, vol. 133(C), pages 1468-1478.
    4. Gaudiosi, Gaetano, 1996. "Offshore wind energy in the world context," Renewable Energy, Elsevier, vol. 9(1), pages 899-904.
    5. Olauson, Jon, 2018. "ERA5: The new champion of wind power modelling?," Renewable Energy, Elsevier, vol. 126(C), pages 322-331.
    6. Ashtine, Masaō & Bello, Richard & Higuchi, Kaz, 2016. "Assessment of wind energy potential over Ontario and Great Lakes using the NARR data: 1980–2012," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 272-282.
    7. Boccard, Nicolas, 2009. "Capacity factor of wind power realized values vs. estimates," Energy Policy, Elsevier, vol. 37(7), pages 2679-2688, July.
    8. Engelhorn, Thorsten & Müsgens, Felix, 2018. "How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany," Energy Economics, Elsevier, vol. 72(C), pages 542-557.
    9. Yamaguchi, Atsushi & Ishihara, Takeshi, 2014. "Assessment of offshore wind energy potential using mesoscale model and geographic information system," Renewable Energy, Elsevier, vol. 69(C), pages 506-515.
    10. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    11. Weisser, D, 2003. "A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function," Renewable Energy, Elsevier, vol. 28(11), pages 1803-1812.
    12. Dahmouni, A.W. & Ben Salah, M. & Askri, F. & Kerkeni, C. & Ben Nasrallah, S., 2011. "Assessment of wind energy potential and optimal electricity generation in Borj-Cedria, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 815-820, January.
    13. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal," Applied Energy, Elsevier, vol. 117(C), pages 116-126.
    14. Ulazia, Alain & Saenz, Jon & Ibarra-Berastegui, Gabriel, 2016. "Sensitivity to the use of 3DVAR data assimilation in a mesoscale model for estimating offshore wind energy potential. A case study of the Iberian northern coastline," Applied Energy, Elsevier, vol. 180(C), pages 617-627.
    15. 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.
    16. Eurek, Kelly & Sullivan, Patrick & Gleason, Michael & Hettinger, Dylan & Heimiller, Donna & Lopez, Anthony, 2017. "An improved global wind resource estimate for integrated assessment models," Energy Economics, Elsevier, vol. 64(C), pages 552-567.
    17. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula," Applied Energy, Elsevier, vol. 134(C), pages 57-64.
    18. Gökçek, Murat & Bayülken, Ahmet & Bekdemir, Şükrü, 2007. "Investigation of wind characteristics and wind energy potential in Kirklareli, Turkey," Renewable Energy, Elsevier, vol. 32(10), pages 1739-1752.
    19. Kecskemety, Krista M. & McNamara, Jack J., 2016. "Influence of wake dynamics on the performance and aeroelasticity of wind turbines," Renewable Energy, Elsevier, vol. 88(C), pages 333-345.
    20. Esteban, Miguel & Leary, David, 2012. "Current developments and future prospects of offshore wind and ocean energy," Applied Energy, Elsevier, vol. 90(1), pages 128-136.
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    Keywords

    Wind energy potential; Air density; ERA5; Fluid mechanics;
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