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On the influence of wind speed model resolution on the global technical wind energy potential

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  • Jung, Christopher
  • Schindler, Dirk

Abstract

Previous estimations of the global technical onshore wind energy potential (WEP) range between 64 and 690 PWh/yr. The diversity of WEP estimates is caused by various applied wind resource data sets, geographical restrictions, and wind turbine features. So far, little attention was paid to the wind speed model resolution and hub height influence on national and global WEP. Thus, this study's goals were to compare WEP estimates from highly and coarsely resolved wind speed data in 120 and 140 m hub height. The wind resource was assessed based on ERA5 wind speed time series at a horizontal resolution of 0.25° × 0.25° and L-moments from the highly resolved Global Wind Speed Model (GloWiSMo) available at 250 m × 250 m horizontal resolution. Theoretical distributions and a generic 3.3 MW wind turbine power curve were used to estimate the average annual energy yield at a 1000 m × 1000 m global grid. A total of twelve geographical restrictions were specified to exclude inaccessible areas from WEP estimations. Using highly resolved wind speed data at 120 m hub height, global WEP was estimated to be 404 PWh/yr. It decreases by 16.1% (339 PWh/yr) using ERA-5 wind speed data, whereas, at 140 m hub height, WEP increases by 11.8% (452 PWh/yr). The results presented highlight the relevance of spatial resolution of wind speed data for wind resource assessment from local to global scales.

Suggested Citation

  • Jung, Christopher & Schindler, Dirk, 2022. "On the influence of wind speed model resolution on the global technical wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:rensus:v:156:y:2022:i:c:s1364032121012648
    DOI: 10.1016/j.rser.2021.112001
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    Cited by:

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    2. Fernando Martins & Pedro Moura & Aníbal T. de Almeida, 2022. "The Role of Electrification in the Decarbonization of the Energy Sector in Portugal," Energies, MDPI, vol. 15(5), pages 1-35, February.
    3. Gunnell, Yanni & Mietton, Michel & Touré, Amadou Abdourhamane & Fujiki, Kenji, 2023. "Potential for wind farming in West Africa from an analysis of daily peak wind speeds and a review of low-level jet dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    4. Jung, Christopher & Schindler, Dirk, 2023. "Introducing a new wind speed complementarity model," Energy, Elsevier, vol. 265(C).
    5. José Rafael Dorrego Portela & Geovanni Hernández Galvez & Quetzalcoatl Hernandez-Escobedo & Ricardo Saldaña Flores & Omar Sarracino Martínez & Orlando Lastres Danguillecourt & Pascual López de Paz & A, 2022. "Microscale Wind Assessment, Comparing Mesoscale Information and Observed Wind Data," Sustainability, MDPI, vol. 14(19), pages 1-12, September.

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    Keywords

    Wind power; ERA5; GIS; Wind resource assessment; Hub height;
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