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Performance prediction of active pitch-regulated wind turbine with short duration variations in source wind

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  • Roy, Sanjoy

Abstract

Short duration wind variations affect real time performance of active pitch-regulated wind turbines in two ways as evident from reported experimental and empirical studies. First the mean output power, which may be referred to as the short duration output power, differs significantly from the corresponding zero-turbulence value obtained with ideal source wind streamlines. Second, random variation of output around the mean value appears with a significant standard deviation; the normalised value of which is referred to as the short duration variability. In this paper, analytical interpretation of both metrics is presented under assumption of two-parameter Weibull statistics for short duration wind variations. Statistical estimates for the metrics are presented for conditions described by the well known IEC 61400-1 Standards. Finally the statistical estimation procedure is applied to a Vestas V90 3MW zero-turbulence output curve as an illustrative application example.

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  • Roy, Sanjoy, 2014. "Performance prediction of active pitch-regulated wind turbine with short duration variations in source wind," Applied Energy, Elsevier, vol. 114(C), pages 700-708.
  • Handle: RePEc:eee:appene:v:114:y:2014:i:c:p:700-708
    DOI: 10.1016/j.apenergy.2013.10.009
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    1. Lin, Jin & Sun, Yuan-zhang & Cheng, Lin & Gao, Wen-zhong, 2012. "Assessment of the power reduction of wind farms under extreme wind condition by a high resolution simulation model," Applied Energy, Elsevier, vol. 96(C), pages 21-32.
    2. Bessa, Ricardo J. & Miranda, V. & Botterud, A. & Zhou, Z. & Wang, J., 2012. "Time-adaptive quantile-copula for wind power probabilistic forecasting," Renewable Energy, Elsevier, vol. 40(1), pages 29-39.
    3. Vilar, Carolina & Amarís, Hortensia & Usaola, Julio, 2006. "Assessment of flicker limits compliance for wind energy conversion system in the frequency domain," Renewable Energy, Elsevier, vol. 31(8), pages 1089-1106.
    4. Mabel, M. Carolin & Raj, R. Edwin & Fernandez, E., 2010. "Adequacy evaluation of wind power generation systems," Energy, Elsevier, vol. 35(12), pages 5217-5222.
    5. 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.
    6. Pinson, P. & Girard, R., 2012. "Evaluating the quality of scenarios of short-term wind power generation," Applied Energy, Elsevier, vol. 96(C), pages 12-20.
    7. 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.
    8. Hagspiel, Simeon & Papaemannouil, Antonis & Schmid, Matthias & Andersson, Göran, 2012. "Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid," Applied Energy, Elsevier, vol. 96(C), pages 33-44.
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    Cited by:

    1. Astolfi, Davide & Castellani, Francesco & Garinei, Alberto & Terzi, Ludovico, 2015. "Data mining techniques for performance analysis of onshore wind farms," Applied Energy, Elsevier, vol. 148(C), pages 220-233.
    2. Huang, Y. & Wang, Y.D. & Chen, Haisheng & Zhang, Xinjing & Mondol, J. & Shah, N. & Hewitt, N.J., 2017. "Performance analysis of biofuel fired trigeneration systems with energy storage for remote households," Applied Energy, Elsevier, vol. 186(P3), pages 530-538.
    3. Dai, Juchuan & Liu, Deshun & Wen, Li & Long, Xin, 2016. "Research on power coefficient of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 86(C), pages 206-215.

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