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• W2559955929 abstract "Having an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turbine under test conditions is presented. Here, the confidence band is bound by two curves which are estimated using parametric statistical inference techniques. However, the observations that are used for carrying out the statistical analysis are obtained by using the binning method, and in each bin, the outliers are eliminated by using a censorship process based on robust statistical techniques. Then, the observations that are not outliers are divided into observation sets. Finally, both the power curve of the wind turbine and the two curves that define the robust confidence band are estimated using each of the previously mentioned observation sets." @default.
• W2559955929 created "2016-12-16" @default.
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• W2559955929 date "2016-12-07" @default.
• W2559955929 modified "2023-10-06" @default.
• W2559955929 title "Modeling of a Robust Confidence Band for the Power Curve of a Wind Turbine" @default.
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• W2559955929 doi "https://doi.org/10.3390/s16122080" @default.
• W2559955929 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5191061" @default.
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