Reads wind efficiency curve(s) specified in curve_name.

Parameters:curve_name (str or list(str)) – Specifies the curve. Use ‘all’ to get all curves in a MultiIndex DataFrame or one of the curve names to retrieve a single curve. Default: ‘all’.
Returns:Wind efficiency curve. Contains ‘wind_speed’ and ‘efficiency’ columns with wind speed in m/s and wind efficiency (dimensionless). If curve_name is ‘all’ or a list of strings a MultiIndex DataFrame is returned with curve names in the first level of the columns.
Return type:pandas.DataFrame


The wind efficiency curves were generated in the “Dena Netzstudie” [1] and in the work of Kaspar Knorr [2]. The mean wind efficiency curve is an average curve from 12 wind farm distributed over Germany [1] or respectively an average from over 2000 wind farms in Germany [2]. Curves with the appendix ‘extreme’ are wind efficiency curves of single wind farms that are extremely deviating from the respective mean wind efficiency curve. For more information see [1] and [2].


[1](1, 2, 3) Kohler “dena-Netzstudie II. Integration erneuerbarer Energien in die deutsche Stromversorgung im Zeitraum 2015 – 2020 mit Ausblick 2025.”, Deutsche Energie-Agentur GmbH (dena), Tech. rept., 2010, p. 101
[2](1, 2, 3) Knorr, K.: “Modellierung von raum-zeitlichen Eigenschaften der Windenergieeinspeisung für wetterdatenbasierte Windleistungssimulationen”. Universität Kassel, Diss., 2016, p. 124


# Example to plot all curves
fig, ax = plt.subplots() /n
df = get_wind_efficiency_curve(curve_name='all')
for t in df.columns.get_level_values(0).unique():
    p = df[t].set_index('wind_speed')['efficiency'] = t
    ax = p.plot(ax=ax, legend=True)