def test_power_coefficient_curve_output_types(self):
     """
     Test wind_speed as np.array with density and power_coefficient_curve
     as np.array and pd.Series
     """
     assert isinstance(power_coefficient_curve(**self.parameters),
                       pd.Series)
     self.parameters["wind_speed"] = np.array(self.parameters["wind_speed"])
     assert isinstance(power_coefficient_curve(**self.parameters),
                       np.ndarray)
 def test_power_coefficient_curve_2(self):
     """TODO: Explain this test"""
     parameters = self.parameters
     power_output_exp = np.array([0.0, 244615.399, 0.0])
     parameters["wind_speed"] = np.array(parameters["wind_speed"])
     assert_allclose(power_coefficient_curve(**parameters),
                     power_output_exp)
     parameters["density"] = pd.Series(data=parameters["density"])
     assert_allclose(power_coefficient_curve(**parameters),
                     power_output_exp)
     assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
     parameters["power_coefficient_curve_wind_speeds"] = pd.Series(
         data=parameters["power_coefficient_curve_wind_speeds"])
     parameters["power_coefficient_curve_values"] = pd.Series(
         data=parameters["power_coefficient_curve_values"])
     assert_allclose(power_coefficient_curve(**parameters),
                     power_output_exp)
     assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
    def test_power_coefficient_curve_1(self):
        """
        Test wind_speed as pd.Series with density and power_coefficient_curve
        as pd.Series and np.array
        """
        power_output_exp = pd.Series(data=[0.0, 244615.399, 0.0],
                                     name="feedin_power_plant")
        assert_series_equal(power_coefficient_curve(**self.parameters),
                            power_output_exp)

        parameters = self.parameters
        parameters["density"].to_numpy()
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)

        parameters["power_coefficient_curve_values"] = np.array(
            parameters["power_coefficient_curve_values"])
        parameters["power_coefficient_curve_wind_speeds"] = np.array(
            parameters["power_coefficient_curve_wind_speeds"])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
    def test_power_coefficient_curve(self):
        parameters = {'wind_speed': pd.Series(data=[2.0, 5.5, 7.0]),
                      'density': pd.Series(data=[1.3, 1.3, 1.3]),
                      'rotor_diameter': 80,
                      'power_coefficient_curve_wind_speeds':
                          pd.Series([4.0, 5.0, 6.0]),
                      'power_coefficient_curve_values':
                          pd.Series([0.3, 0.4, 0.5])}

        # Test wind_speed as pd.Series with density and power_coefficient_curve
        # as pd.Series and np.array
        power_output_exp = pd.Series(data=[0.0, 244615.399, 0.0],
                                     name='feedin_power_plant')
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        parameters['density'] = np.array(parameters['density'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        parameters['power_coefficient_curve_values'] = np.array(
            parameters['power_coefficient_curve_values'])
        parameters['power_coefficient_curve_wind_speeds'] = np.array(
            parameters['power_coefficient_curve_wind_speeds'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        # Test wind_speed as np.array with density and power_coefficient_curve
        # as np.array and pd.Series
        power_output_exp = np.array([0.0, 244615.399, 0.0])
        parameters['wind_speed'] = np.array(parameters['wind_speed'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
        parameters['density'] = pd.Series(data=parameters['density'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
        parameters['power_coefficient_curve_wind_speeds'] = pd.Series(
            data=parameters['power_coefficient_curve_wind_speeds'])
        parameters['power_coefficient_curve_values'] = pd.Series(
            data=parameters['power_coefficient_curve_values'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
示例#5
0
    def calculate_power_output(self, wind_speed_hub, density_hub):
        r"""
        Calculates the power output of the wind power plant.

        The method specified by the parameter `power_output_model` is used.

        Parameters
        ----------
        wind_speed_hub : :pandas:`pandas.Series<series>` or numpy.array
            Wind speed at hub height in m/s.
        density_hub : :pandas:`pandas.Series<series>` or numpy.array
            Density of air at hub height in kg/m³.

        Returns
        -------
        :pandas:`pandas.Series<series>`
            Electrical power output of the wind turbine in W.

        """
        if self.power_output_model == "power_curve":
            if self.power_plant.power_curve is None:
                raise TypeError("Power curve values of {} are missing.".format(
                    self.power_plant))
            logging.debug("Calculating power output using power curve.")
            return power_output.power_curve(
                wind_speed_hub,
                self.power_plant.power_curve["wind_speed"],
                self.power_plant.power_curve["value"],
                density_hub,
                self.density_correction,
            )
        elif self.power_output_model == "power_coefficient_curve":
            if self.power_plant.power_coefficient_curve is None:
                raise TypeError("Power coefficient curve values of {} are "
                                "missing.".format(self.power_plant))
            logging.debug("Calculating power output using power coefficient "
                          "curve.")
            return power_output.power_coefficient_curve(
                wind_speed_hub,
                self.power_plant.power_coefficient_curve["wind_speed"],
                self.power_plant.power_coefficient_curve["value"],
                self.power_plant.rotor_diameter,
                density_hub,
            )
        else:
            raise ValueError(
                "'{0}' is an invalid value. ".format(self.power_output_model) +
                "`power_output_model` must be " +
                "'power_curve' or 'power_coefficient_curve'.")
示例#6
0
    def calculate_power_output(self, wind_speed_hub, density_hub):
        r"""
        Calculates the power output of the wind power plant.

        The method specified by the parameter `power_output_model` is used.

        Parameters
        ----------
        wind_speed_hub : pandas.Series or numpy.array
            Wind speed at hub height in m/s.
        density_hub : pandas.Series or numpy.array
            Density of air at hub height in kg/m³.

        Returns
        -------
        pandas.Series
            Electrical power output of the wind turbine in W.

        """
        if self.power_output_model == 'power_curve':
            if self.power_plant.power_curve is None:
                raise TypeError("Power curve values of " +
                                self.power_plant.name + " are missing.")
            logging.debug('Calculating power output using power curve.')
            return (power_output.power_curve(
                wind_speed_hub, self.power_plant.power_curve['wind_speed'],
                self.power_plant.power_curve['value'], density_hub,
                self.density_correction))
        elif self.power_output_model == 'power_coefficient_curve':
            if self.power_plant.power_coefficient_curve is None:
                raise TypeError("Power coefficient curve values of " +
                                self.power_plant.name + " are missing.")
            logging.debug('Calculating power output using power coefficient '
                          'curve.')
            return (power_output.power_coefficient_curve(
                wind_speed_hub,
                self.power_plant.power_coefficient_curve['wind_speed'],
                self.power_plant.power_coefficient_curve['value'],
                self.power_plant.rotor_diameter, density_hub))
        else:
            raise ValueError(
                "'{0}' is an invalid value. ".format(self.power_output_model) +
                "`power_output_model` must be " +
                "'power_curve' or 'power_coefficient_curve'.")
示例#7
0
    def test_power_coefficient_curve(self):
        parameters = {
            'wind_speed': pd.Series(data=[2.0, 5.5, 7.0]),
            'density': pd.Series(data=[1.3, 1.3, 1.3]),
            'rotor_diameter': 80,
            'power_coefficient_curve_wind_speeds': pd.Series([4.0, 5.0, 6.0]),
            'power_coefficient_curve_values': pd.Series([0.3, 0.4, 0.5])
        }

        # Tests without density correction:
        # Test wind_speed as pd.Series with density and power_coefficient_curve
        # as pd.Series and np.array
        power_output_exp = pd.Series(data=[0.0, 244615.399, 0.0],
                                     name='feedin_wind_turbine')
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        parameters['density'] = np.array(parameters['density'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        parameters['power_coefficient_curve_values'] = np.array(
            parameters['power_coefficient_curve_values'])
        parameters['power_coefficient_curve_wind_speeds'] = np.array(
            parameters['power_coefficient_curve_wind_speeds'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        # Test wind_speed as np.array with density and power_coefficient_curve
        # as np.array and pd.Series
        power_output_exp = np.array([0.0, 244615.399, 0.0])
        parameters['wind_speed'] = np.array(parameters['wind_speed'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
        parameters['density'] = pd.Series(data=parameters['density'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
        parameters['power_coefficient_curve_wind_speeds'] = pd.Series(
            data=parameters['power_coefficient_curve_wind_speeds'])
        parameters['power_coefficient_curve_values'] = pd.Series(
            data=parameters['power_coefficient_curve_values'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)

        # Tests with density correction:
        # Test wind_speed as np.array with density and power_coefficient_curve
        # as pd.Series and np.array
        power_output_exp = np.array([0.0, 262869.785, 0.0])
        parameters['density_correction'] = True
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
        parameters['density'] = np.array(parameters['density'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)
        parameters['power_coefficient_curve_values'] = np.array(
            parameters['power_coefficient_curve_values'])
        parameters['power_coefficient_curve_wind_speeds'] = np.array(
            parameters['power_coefficient_curve_wind_speeds'])
        assert_allclose(power_coefficient_curve(**parameters),
                        power_output_exp)
        assert isinstance(power_coefficient_curve(**parameters), np.ndarray)

        # Test wind_speed as pd.Series with density and power_coefficient_curve
        # as np. array and pd.Series
        power_output_exp = pd.Series(data=[0.0, 262869.785, 0.0],
                                     name='feedin_wind_turbine')
        parameters['wind_speed'] = pd.Series(data=parameters['wind_speed'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        parameters['density'] = pd.Series(data=parameters['density'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)
        parameters['power_coefficient_curve_wind_speeds'] = pd.Series(
            data=parameters['power_coefficient_curve_wind_speeds'])
        parameters['power_coefficient_curve_values'] = pd.Series(
            data=parameters['power_coefficient_curve_values'])
        assert_series_equal(power_coefficient_curve(**parameters),
                            power_output_exp)

        # Raise TypeErrors due to wrong type of `density_correction`
        with pytest.raises(TypeError):
            parameters['density'] = 'wrong_type'
            power_coefficient_curve(**parameters)