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Wind energy potential assessment considering the uncertainties due to limited data

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  • Jung, Sungmoon
  • Arda Vanli, O.
  • Kwon, Soon-Duck

Abstract

A new Bayesian approach is proposed to estimate the annual energy production (AEP) of a site where construction of wind turbines is considered. The approach uses long-term wind speeds of a nearby weather station and short-term wind speeds near the target site. Uncertainties exist due to the limited amount of data in the target site, in addition to the inherent uncertainties in the wind speed, the air density, the surface roughness exponent, and the power performance of the turbine. The proposed method systematically addresses these uncertainties and provides the distribution of the AEP. For illustration, we used the wind speed data near Yeosu, Korea, and the power performance curve of a 3MW turbine. For the site and the turbine studied, the range given by the 95% confidence interval corresponded to 8.9% of the mean AEP, and the range given by the 99% confidence interval corresponded to 11.9% of the mean AEP. Benefits of using the Bayesian approach compared to the classical statistical inference was also illustrated with the case study. The proposed approach provides a more conservative estimation considering the uncertainties due to the limited amount of data. Distributions of parameters of the prediction model are also provided, which enables a more detailed analysis of the prediction.

Suggested Citation

  • Jung, Sungmoon & Arda Vanli, O. & Kwon, Soon-Duck, 2013. "Wind energy potential assessment considering the uncertainties due to limited data," Applied Energy, Elsevier, vol. 102(C), pages 1492-1503.
    • Handle: RePEc:eee:appene:v:102:y:2013:i:c:p:1492-1503
    DOI: 10.1016/j.apenergy.2012.09.011
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    References listed on IDEAS

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    1. Fyrippis, Ioannis & Axaopoulos, Petros J. & Panayiotou, Gregoris, 2010. "Wind energy potential assessment in Naxos Island, Greece," Applied Energy, Elsevier, vol. 87(2), pages 577-586, February.
    2. Fadare, D.A., 2010. "The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria," Applied Energy, Elsevier, vol. 87(3), pages 934-942, March.
    3. Lackner, Matthew A. & Rogers, Anthony L. & Manwell, James F. & McGowan, Jon G., 2010. "A new method for improved hub height mean wind speed estimates using short-term hub height data," Renewable Energy, Elsevier, vol. 35(10), pages 2340-2347.
    4. Ucar, Aynur & Balo, Figen, 2009. "Evaluation of wind energy potential and electricity generation at six locations in Turkey," Applied Energy, Elsevier, vol. 86(10), pages 1864-1872, October.
    5. Kwon, Soon-Duck, 2010. "Uncertainty analysis of wind energy potential assessment," Applied Energy, Elsevier, vol. 87(3), pages 856-865, March.
    6. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    7. Costa, Alexandre & Crespo, Antonio & Navarro, Jorge & Lizcano, Gil & Madsen, Henrik & Feitosa, Everaldo, 2008. "A review on the young history of the wind power short-term prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(6), pages 1725-1744, August.
    8. Rehman, Shafiqur & Ahmad, Aftab, 2004. "Assessment of wind energy potential for coastal locations of the Kingdom of Saudi Arabia," Energy, Elsevier, vol. 29(8), pages 1105-1115.
    9. Lei, Ma & Shiyan, Luan & Chuanwen, Jiang & Hongling, Liu & Yan, Zhang, 2009. "A review on the forecasting of wind speed and generated power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 915-920, May.
    10. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    11. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    12. Bekele, Getachew & Palm, Björn, 2009. "Wind energy potential assessment at four typical locations in Ethiopia," Applied Energy, Elsevier, vol. 86(3), pages 388-396, March.
    13. Ramachandra, T.V. & Subramanian, D.K. & Joshi, N.V., 1997. "Wind energy potential assessment in Uttara Kannada district of Karnataka, India," Renewable Energy, Elsevier, vol. 10(4), pages 585-611.
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