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Review of power curve modelling for wind turbines

Author

Listed:
  • Carrillo, C.
  • Obando Montaño, A.F.
  • Cidrás, J.
  • Díaz-Dorado, E.

Abstract

Currently, variable speed wind turbine generators (VSWTs) are the type of wind turbines most widely installed. For wind energy studies, they are usually modelled by means the approximation of the manufacturer power curve using a generic equation. In literature, several expressions to do this approximation can be found; nevertheless, there is not much information about which is the most appropriate to represent the energy produced by a VSWT. For this reason, in this paper, it is carried out a review of the equations commonly used to represent the power curves of VSWTs: polynomial power curve, exponential power curve, cubic power curve and approximate cubic power curve. They have been compared to manufacturer power curves by using the coefficients of determination, as fitness indicators, and by using the estimation of energy production. Data gathered from nearly 200 commercial VSWTs, ranging from 225 to 7500kW, has been used for this analysis. Results of the analysis presented in the paper show that exponential and cubic approximations give the higher R2 values and the lower error in energy estimation. With the approximate cubic power curve quite high values of R2 and low errors in energy estimation are achieved, which makes this kind of approximation very interesting due to its simplicity. Finally, the polynomial power curve shows the worst results mainly due to its sensitivity to the data given by the manufacturer.

Suggested Citation

  • Carrillo, C. & Obando Montaño, A.F. & Cidrás, J. & Díaz-Dorado, E., 2013. "Review of power curve modelling for wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 572-581.
  • Handle: RePEc:eee:rensus:v:21:y:2013:i:c:p:572-581
    DOI: 10.1016/j.rser.2013.01.012
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    References listed on IDEAS

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    1. Jowder, Fawzi A.L., 2009. "Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain," Applied Energy, Elsevier, vol. 86(4), pages 538-545, April.
    2. Wen, Jiang & Zheng, Yan & Donghan, Feng, 2009. "A review on reliability assessment for wind power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2485-2494, December.
    3. Thapar, Vinay & Agnihotri, Gayatri & Sethi, Vinod Krishna, 2011. "Critical analysis of methods for mathematical modelling of wind turbines," Renewable Energy, Elsevier, vol. 36(11), pages 3166-3177.
    4. Carrillo, C. & Feijóo, A. & Cidrás, J., 2009. "Comparative study of flywheel systems in an isolated wind plant," Renewable Energy, Elsevier, vol. 34(3), pages 890-898.
    5. 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.
    6. Hu, Ssu-yuan & Cheng, Jung-ho, 2007. "Performance evaluation of pairing between sites and wind turbines," Renewable Energy, Elsevier, vol. 32(11), pages 1934-1947.
    7. EL-Shimy, M., 2010. "Optimal site matching of wind turbine generator: Case study of the Gulf of Suez region in Egypt," Renewable Energy, Elsevier, vol. 35(8), pages 1870-1878.
    Full references (including those not matched with items on IDEAS)

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