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The importance of accurate wind resource assessment for evaluating the economic viability of small wind turbines

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  • Drew, D.R.
  • Barlow, J.F.
  • Cockerill, T.T.
  • Vahdati, M.M.

Abstract

The techno-economic performance of a small wind turbine is very sensitive to the available wind resource. However, due to financial and practical constraints installers rely on low resolution wind speed databases to assess a potential site. This study investigates whether the two site assessment tools currently used in the UK, NOABL or the Energy Saving Trust wind speed estimator, are accurate enough to estimate the techno-economic performance of a small wind turbine. Both the tools tend to overestimate the wind speed, with a mean error of 23% and 18% for the NOABL and Energy Saving Trust tool respectively. A techno-economic assessment of 33 small wind turbines at each site has shown that these errors can have a significant impact on the estimated load factor of an installation. Consequently, site/turbine combinations which are not economically viable can be predicted to be viable. Furthermore, both models tend to underestimate the wind resource at relatively high wind speed sites, this can lead to missed opportunities as economically viable turbine/site combinations are predicted to be non-viable. These results show that a better understanding of the local wind resource is a required to make small wind turbines a viable technology in the UK.

Suggested Citation

  • Drew, D.R. & Barlow, J.F. & Cockerill, T.T. & Vahdati, M.M., 2015. "The importance of accurate wind resource assessment for evaluating the economic viability of small wind turbines," Renewable Energy, Elsevier, vol. 77(C), pages 493-500.
    • Handle: RePEc:eee:renene:v:77:y:2015:i:c:p:493-500
    DOI: 10.1016/j.renene.2014.12.032
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    Cited by:

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    2. Ijjou Tizgui & Fatima El Guezar & Hassane Bouzahir & Alessandro N. Vargas, 2018. "Estimation and Analysis of Wind Electricity Production Cost in Morocco," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 58-66.
    3. Nedaei, Mojtaba & Assareh, Ehsanolah & Walsh, Philip R., 2018. "A comprehensive evaluation of the wind resource characteristics to investigate the short term penetration of regional wind power based on different probability statistical methods," Renewable Energy, Elsevier, vol. 128(PA), pages 362-374.
    4. Wolf-Gerrit Früh, 2023. "Assessing the Performance of Small Wind Energy Systems Using Regional Weather Data," Energies, MDPI, vol. 16(8), pages 1-21, April.
    5. José V. P. Miguel & Eliane A. Fadigas & Ildo L. Sauer, 2019. "The Influence of the Wind Measurement Campaign Duration on a Measure-Correlate-Predict (MCP)-Based Wind Resource Assessment," Energies, MDPI, vol. 12(19), pages 1-15, September.
    6. Murthy, K.S.R. & Rahi, O.P., 2016. "Preliminary assessment of wind power potential over the coastal region of Bheemunipatnam in northern Andhra Pradesh, India," Renewable Energy, Elsevier, vol. 99(C), pages 1137-1145.
    7. Kumar, Rakesh & Raahemifar, Kaamran & Fung, Alan S., 2018. "A critical review of vertical axis wind turbines for urban applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 281-291.
    8. Elshafei, Basem & Peña, Alfredo & Popov, Atanas & Giddings, Donald & Ren, Jie & Xu, Dong & Mao, Xuerui, 2023. "Offshore wind resource assessment based on scarce spatio-temporal measurements using matrix factorization," Renewable Energy, Elsevier, vol. 202(C), pages 1215-1225.

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    Microgeneration; Wind; Resource;
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