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Minor changes in docstrings
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example/basic_example.py

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@@ -171,7 +171,7 @@ def calculate_power_output(weather, my_turbine, e126):
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# initialise ModelChain with own specifications and use run_model method
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# to calculate power output
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mc_e126 = ModelChain(e126, **modelchain_data).run_model(weather)
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# write power output timeseries to WindTurbine object
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# write power output time series to WindTurbine object
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e126.power_output = mc_e126.power_output
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return

windpowerlib/wind_farm.py

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@@ -99,9 +99,10 @@ def mean_hub_height(self):
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Calculates the mean hub height of the wind farm.
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The mean hub height of a wind farm is necessary for power output
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calculations with an aggregated wind farm power curve. Hub heights of
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wind turbines with higher nominal power weigh more than others.
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Assigns the hub height to the wind farm object.
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calculations with an aggregated wind farm power curve containing wind
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turbines with different hub heights. Hub heights of wind turbines with
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higher nominal power weigh more than others. Assigns the hub height to
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the wind farm object.
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Returns
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-------
@@ -140,7 +141,7 @@ def get_installed_power(self):
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The installed power of wind farms is necessary when a
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:class:`~.wind_turbine_cluster.WindTurbineCluster` object is used and
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is power weighed mean hub height is calcuated with
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it's power weighed mean hub height is calculated with
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:py:func:`~.wind_turbine_cluster.WindTurbineCluster.mean_hub_height`.
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Returns

windpowerlib/wind_turbine_cluster.py

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@@ -2,7 +2,7 @@
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The ``wind_turbine_cluster`` module contains the class WindTurbineCluster that
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implements a wind turbine cluster in the windpowerlib and functions needed for
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the modelling of a wind turbine cluster.
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A wind turbine cluster comprises wind turbines belonging to the same weather
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A wind turbine cluster comprises wind farms belonging to the same weather
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data grid point.
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"""

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