pywasp.px_aep

pywasp.px_aep(uncertainty_table, ds_net_aep, sensitivity_factor=1.5, percentile=90)[source]

Calculates the Annual Energy Production (AEP) level reached with a given probability.

Parameters:

  • uncertainty_table (DataFrame) – The DataFrame containing the uncertainties.

  • ds_net_aep (xarray.Dataset) – The dataset containing the net_aep and net_aep_sector values.

  • sensitivity_factor (float) – The sensitivity factor value can either be calculated with the sensitivity_factor function or given directly. Default is 1.5. Use of sensitivity_factor is recommended.

  • percentile (int) – The exceedance probability corresponding to our desired Pxx percentile. Default is 90 in order to calcualte p90 (AEP value with a chance of being surpassed 90% of the times).

Returns:

xarray.Dataset – The updated dataset including the Px and Px_sector values.

Raises:

ValueError – If net_aep and net_aep_sector are not in the ds_net_aep dataset.

Notes

  • The function first validates the uncertainty table. See validate_uncertainty_table function.

  • The function will be executed even if one out of the two net_aep variables is missing.

I.e, if net_aep_sector is missing the function will still calculate and append the Px for all sectors and vice versa.

Examples

>>> uncertainty_table = get_uncertainty_table('dtu_default')
>>> sensitivity_factor = sensitivity_factor(pwc, wtg, wind_perturbation_factor=0.05)
>>> ds_net_aep = net_aep(uncertainty_table, ds_potential_aep)
>>> px_aep(uncertainty_table, sensitivity_factor, ds_net_aep, percentile=90)