Improve error raising

Author: birgits

windpowerlib/turbine_cluster_modelchain.py

@@ -182,6 +182,10 @@ def assign_power_curve(self, weather_df):
             weather_df['turbulence_intensity'].values.mean() if
             'turbulence_intensity' in
             weather_df.columns.get_level_values(0) else None)
+        roughness_length = (
+            weather_df['roughness_length'].values.mean() if
+            'roughness_length' in weather_df.columns.get_level_values(0) else
+            None)
         # Assign power curve
         if (self.wake_losses_model == 'wind_farm_efficiency' or
                 self.wake_losses_model is None):
@@ -200,7 +204,7 @@ def assign_power_curve(self, weather_df):
             smoothing=self.smoothing, block_width=self.block_width,
             standard_deviation_method=self.standard_deviation_method,
             smoothing_order=self.smoothing_order,
-            roughness_length=weather_df['roughness_length'][0].mean(),
+            roughness_length=roughness_length,
             turbulence_intensity=turbulence_intensity)
         # Further logging messages
         if self.smoothing is False:

windpowerlib/wind_farm.py

@@ -253,7 +253,8 @@ def assign_power_curve(self, wake_losses_model='wind_farm_efficiency',
             if smoothing:
                 if (standard_deviation_method == 'turbulence_intensity' and
                         turbulence_intensity is None):
-                    if 'roughness_length' in kwargs:
+                    if 'roughness_length' in kwargs and \
+                            kwargs['roughness_length'] is not None:
                         # Calculate turbulence intensity and write to kwargs
                         turbulence_intensity = (
                             tools.estimate_turbulence_intensity(