brightwind.analyse.analyse.TI.by_speed

static TI.by_speed(wspd, wspd_std, speed_bin_array=array([-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5, 22.5, 23.5, 24.5, 25.5, 26.5, 27.5, 28.5, 29.5, 30.5, 31.5, 32.5, 33.5, 34.5, 35.5, 36.5, 37.5, 38.5, 39.5, 40.5]), speed_bin_labels=range(0, 41), percentile=90, IEC_class=None, return_data=False)

Accepts a wind speed series and its standard deviation, calculates turbulence intensity (TI) and returns the distribution by of TI by speed bins

Parameters

  • wspd (pandas.Series) – Wind speed data series

  • wspd_std (pandas.Series) – Wind speed standard deviation data series

  • speed_bin_array (List or array) – (Optional) Array of wind speeds where adjacent elements of array form a bin

  • speed_bin_labels (List, range or array) – (Optional) Labels to use for speed bins, 0, 1, 2, 3 .. and so on by default

  • percentile (float, int) – The percentile representative of TI (see return for more information)

  • IEC_class – By default IEC class 2005 is used for custom class pass a DataFrame. Note we have removed option to include IEC Class 1999 as no longer appropriate. This may need to be placed in a separate function when updated IEC standard is released

  • return_data (bool) – Set to True if you want the data returned.

Returns

TI distribution with columns names as:

  • Mean_TI (average TI for a speed bin),

  • TI_Count ( number of data points in the bin),

  • Rep_TI (Representative TI set at 90 percentile by default,

  • TI_2Sigma (2 sigma TI),

  • Char_TI (characteristic TI)

Return type

pandas.DataFrame