Merge branch 'features/tools' into dev

Author: SabineHaas

windpowerlib/modelchain.py

@@ -23,7 +23,8 @@ class ModelChain(object):
     wind_speed_model : string
         Parameter to define which model to use to calculate the wind speed at
         hub height. Valid options are 'logarithmic', 'hellman' and
-        'interpolation_extrapolation'. Default: 'logarithmic'.
+        'interpolation_extrapolation', 'log_interpolation_extrapolation'.
+        Default: 'logarithmic'.
     temperature_model : string
         Parameter to define which model to use to calculate the temperature of
         air at hub height. Valid options are 'linear_gradient' and
@@ -55,7 +56,8 @@ class ModelChain(object):
     wind_speed_model : string
         Parameter to define which model to use to calculate the wind speed at
         hub height. Valid options are 'logarithmic', 'hellman' and
-        'interpolation_extrapolation'. Default: 'logarithmic'.
+        'interpolation_extrapolation', 'log_interpolation_extrapolation'.
+        Default: 'logarithmic'.
     temperature_model : string
         Parameter to define which model to use to calculate the temperature of
         air at hub height. Valid options are 'linear_gradient' and
@@ -300,6 +302,11 @@ def wind_speed_hub(self, weather_df):
                           'extrapolation.')
             wind_speed_hub = tools.linear_interpolation_extrapolation(
                 weather_df['wind_speed'], self.wind_turbine.hub_height)
+        elif self.wind_speed_model == 'log_interpolation_extrapolation':
+            logging.debug('Calculating wind speed using logarithmic inter- or '
+                          'extrapolation.')
+            wind_speed_hub = tools.logarithmic_interpolation_extrapolation(
+                weather_df['wind_speed'], self.wind_turbine.hub_height)
         else:
             raise ValueError("'{0}' is an invalid value. ".format(
                 self.wind_speed_model) + "`wind_speed_model` must be "

windpowerlib/tools.py

@@ -13,7 +13,7 @@
 
 def linear_interpolation_extrapolation(df, target_height):
     r"""
-    Inter- or extrapolates between the values of a data frame.
+    Linear inter- or extrapolates between the values of a data frame.
 
     This function can be used for the inter-/extrapolation of a parameter
     (e.g wind speed) available at two or more different heights, to approximate
@@ -73,6 +73,60 @@ def linear_interpolation_extrapolation(df, target_height):
             (target_height - heights_sorted[0]) + df[heights_sorted[0]])
 
 
+def logarithmic_interpolation_extrapolation(df, target_height):
+    r"""
+    Logarithmic inter- or extrapolates between the values of a data frame.
+
+    This function can be used for the inter-/extrapolation of the wind speed if
+    it is available at two or more different heights, to approximate
+    the value at hub height. The function is carried out when the parameter
+    `wind_speed_model` :class:`~.modelchain.ModelChain` class is
+    'log_interpolation_extrapolation'.
+
+    Parameters
+    ----------
+    df : pandas.DataFrame
+        DataFrame with time series for parameter that is to be interpolated or
+        extrapolated. The columns of the DataFrame are the different heights
+        for which the parameter is available. If more than two heights are
+        given, the two closest heights are used. See example in
+        :py:func:`~.linear_interpolation_extrapolation` on how the
+        DataFrame should look like and how the function can be used.
+    target_height : float
+        Height for which the parameter is approximated (e.g. hub height).
+
+    Returns
+    -------
+    pandas.Series
+        Result of the inter-/extrapolation (e.g. wind speed at hub height).
+
+    Notes
+    -----
+
+    For the logarithmic inter- and extrapolation the following equation is
+    used [1]_:
+
+    .. math:: f(x) = \frac{\ln(x) \cdot (f(x_2) - f(x_1)) - f(x_2) \cdot \ln(x_1) + f(x_1) \cdot \ln(x_2)}{\ln(x_2) - \ln(x_1)}
+
+    References
+    ----------
+    .. [1] Knorr, K.: "Modellierung von raum-zeitlichen Eigenschaften der
+             Windenergieeinspeisung für wetterdatenbasierte
+             Windleistungssimulationen". Universität Kassel, Diss., 2016,
+             p. 83
+
+    """
+    # find closest heights
+    heights_sorted = df.columns[
+        sorted(range(len(df.columns)),
+               key=lambda i: abs(df.columns[i] - target_height))]
+    return ((np.log(target_height) *
+             (df[heights_sorted[1]] - df[heights_sorted[0]]) -
+             df[heights_sorted[1]] * np.log(heights_sorted[0]) +
+             df[heights_sorted[0]] * np.log(heights_sorted[1])) /
+            (np.log(heights_sorted[1]) - np.log(heights_sorted[0])))
+
+
 def gaussian_distribution(function_variable, standard_deviation, mean=0):
     r"""
     Normal distribution or gaussian distribution.
@@ -105,7 +159,7 @@ def gaussian_distribution(function_variable, standard_deviation, mean=0):
     ----------
     .. [1] Berendsen, H.: "A Student's Guide to Data and Error Analysis".
              New York, Cambridge University Press, 2011, p. 37
-    
+
     # TODO: add references
 
     """
@@ -118,6 +172,29 @@ def estimate_turbulence_intensity(height, roughness_length):
     """
     Calculate turbulence intensity.
 
+    Parameters
+    ----------
+    height : Float
+        Height above ground in m at which the turbulence intensity is
+        calculated.
+    roughness_length : pandas.Series or numpy.array or float
+        Roughness length.
+
+    Notes
+    -----
+    The following equation is used [1]_:
+
+    .. math:: TI = \frac{1}{ln \left(\frac{h}{z_\text{0}} \right)}
+
+    with:
+        TI: turbulence intensity, h: height, :math:`z_{0}`: roughness length
+
+    References
+    ----------
+    .. [1] Knorr, K.: "Modellierung von raum-zeitlichen Eigenschaften der
+             Windenergieeinspeisung für wetterdatenbasierte
+             Windleistungssimulationen". Universität Kassel, Diss., 2016,
+             p. 88
+
     """
-    # TODO: Search other possibilities for TI.
     return 1 / (np.log(height / roughness_length))

windpowerlib/wind_speed.py

@@ -42,7 +42,7 @@ def logarithmic_profile(wind_speed, wind_speed_height, hub_height,
 
     Notes
     -----
-    The following equation is used [1]_:
+    The following equation is used [1]_, [2]_, [3]_:
 
     .. math:: v_{wind,hub}=v_{wind,data}\cdot
         \frac{\ln\left(\frac{h_{hub}-d}{z_{0}}\right)}{\ln\left(