Tests for turbine cluster modelchain

Author: SabineHaas

tests/test_turbine_cluster_modelchain.py

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+import pandas as pd
+import numpy as np
+import pytest
+from pandas.util.testing import assert_series_equal
+
+import windpowerlib.wind_farm as wf
+import windpowerlib.wind_turbine as wt
+import windpowerlib.turbine_cluster_modelchain as tc_mc
+
+
+class TestTurbineClusterModelChain:
+
+    @classmethod
+    def setup_class(self):
+        self.test_turbine = {'hub_height': 100,
+                             'rotor_diameter': 80,
+                             'name': 'ENERCON E 126 7500',
+                             'fetch_curve': 'power_curve'}
+        self.test_farm = {'name': 'test farm',
+                          'wind_turbine_fleet': [
+                              {'wind_turbine':
+                                   wt.WindTurbine(**self.test_turbine),
+                               'number_of_turbines': 3}]}
+
+    def test_run_model(self):
+        parameters = {'wake_losses_model': 'dena_mean',
+                      'smoothing': False,
+                      'standard_deviation_method': 'turbulence_intensity',
+                      'smoothing_order': 'wind_farm_power_curves'}
+        temperature_2m = np.array([[267], [268]])
+        temperature_10m = np.array([[267], [266]])
+        pressure_0m = np.array([[101125], [101000]])
+        wind_speed_8m = np.array([[4.0], [5.0]])
+        wind_speed_10m = np.array([[5.0], [6.5]])
+        roughness_length = np.array([[0.15], [0.15]])
+        weather_df = pd.DataFrame(np.hstack((temperature_2m,
+                                             temperature_10m,
+                                             pressure_0m,
+                                             wind_speed_8m,
+                                             wind_speed_10m,
+                                             roughness_length)),
+                                  index=[0, 1],
+                                  columns=[np.array(['temperature',
+                                                     'temperature',
+                                                     'pressure',
+                                                     'wind_speed',
+                                                     'wind_speed',
+                                                     'roughness_length']),
+                                           np.array([2, 10, 0, 8, 10, 0])])
+
+        # Test modelchain with default values
+        power_output_exp = pd.Series(data=[4409211.803349806,
+                                           10212484.219845157],
+                                     name='feedin_power_plant')
+        test_tc_mc = tc_mc.TurbineClusterModelChain(
+            power_plant=wf.WindFarm(**self.test_farm), **parameters)
+        test_tc_mc.run_model(weather_df)
+        assert_series_equal(test_tc_mc.power_output, power_output_exp)
+
+        # Test constant efficiency
+        parameters['wake_losses_model'] = 'constant_efficiency'
+        test_wind_farm = wf.WindFarm(**self.test_farm)
+        test_wind_farm.efficiency = 0.9
+        power_output_exp = pd.Series(data=[4676095.973725522,
+                                           10314411.142196147],
+                                     name='feedin_power_plant')
+        test_tc_mc = tc_mc.TurbineClusterModelChain(
+            power_plant=test_wind_farm, **parameters)
+        test_tc_mc.run_model(weather_df)
+        assert_series_equal(test_tc_mc.power_output, power_output_exp)
+
+        # TODO: Test power efficiency curve?
+
+        # Test smoothing
+        parameters['smoothing'] = 'True'
+        test_wind_farm = wf.WindFarm(**self.test_farm)
+        test_wind_farm.efficiency = 0.9
+        power_output_exp = pd.Series(data=[5015168.554748144,
+                                           10389592.995632712],
+                                     name='feedin_power_plant')
+        test_tc_mc = tc_mc.TurbineClusterModelChain(
+            power_plant=test_wind_farm, **parameters)
+        test_tc_mc.run_model(weather_df)
+        assert_series_equal(test_tc_mc.power_output, power_output_exp)
+
+        # Test other smoothing order # TODO: Test different wind turbines
+        parameters['smoothing_order'] = 'turbine_power_curves'
+        test_wind_farm = wf.WindFarm(**self.test_farm)
+        test_wind_farm.efficiency = 0.9
+        power_output_exp = pd.Series(data=[5015168.554748144,
+                                           10389592.995632712],
+                                     name='feedin_power_plant')
+        test_tc_mc = tc_mc.TurbineClusterModelChain(
+            power_plant=test_wind_farm, **parameters)
+        test_tc_mc.run_model(weather_df)
+        assert_series_equal(test_tc_mc.power_output, power_output_exp)
+
+
+        # TODO: test turbine cluster