How to use the pvlib.irradiance.perez function in pvlib

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github SunPower / pvfactors / pvfactors / tools.py View on Github external
df_inputs_back_surface = df_inputs.loc[sun_hitting_back_surface]
    # Reverse the surface normal to switch to back-surface circumsolar calc
    df_inputs_back_surface.loc[:, 'array_azimuth'] -= 180.
    df_inputs_back_surface.loc[:, 'array_azimuth'] = np.mod(
        df_inputs_back_surface.loc[:, 'array_azimuth'], 360.
    )
    df_inputs_back_surface.loc[:, 'array_tilt'] = (
        180. - df_inputs_back_surface.array_tilt)

    if df_inputs_back_surface.shape[0] > 0:
        # Use recursion to calculate circumsolar luminance for back surface
        df_inputs_back_surface = perez_diffuse_luminance(
            df_inputs_back_surface)

    # Calculate Perez diffuse components
    diffuse_poa, components = irradiance.perez(df_inputs.array_tilt,
                                               df_inputs.array_azimuth,
                                               df_inputs.dhi, df_inputs.dni,
                                               dni_et,
                                               df_inputs.solar_zenith,
                                               df_inputs.solar_azimuth,
                                               am,
                                               return_components=True)

    # Calculate Perez view factors:
    a = aoi_projection(df_inputs.array_tilt, df_inputs.array_azimuth,
                       df_inputs.solar_zenith, df_inputs.solar_azimuth)
    a = np.maximum(a, 0)
    b = cosd(df_inputs.solar_zenith)
    b = np.maximum(b, cosd(85))

    vf_perez = pd.DataFrame(
github oemof / feedinlib / feedinlib / models.py View on Github external
# Determine the extraterrestrial radiation
        data['dni_extra'] = pvlib.irradiance.extraradiation(
            datetime_or_doy=data.index.dayofyear)

        # Determine the relative air mass
        data['airmass'] = pvlib.atmosphere.relativeairmass(data['zenith'])

        # Determine direct normal irradiation
        data['dni'] = (data['dirhi']) / np.sin(np.radians(90 - data['zenith']))

        # what for??
        data['dni'][data['zenith'] > 88] = data['dirhi']

        # Determine the sky diffuse irradiation in plane
        # with model of Perez (modell switch would be good)
        data['poa_sky_diffuse'] = pvlib.irradiance.perez(
            surface_tilt=self.powerplant.tilt,
            surface_azimuth=self.powerplant.azimuth,
            dhi=data['dhi'],
            dni=data['dni'],
            dni_extra=data['dni_extra'],
            solar_zenith=data['zenith'],
            solar_azimuth=data['azimuth'],
            airmass=data['airmass'])

        # Set NaN values to zero
        data['poa_sky_diffuse'][
            pd.isnull(data['poa_sky_diffuse'])] = 0

        # Determine the diffuse irradiation from ground reflection in plane
        data['poa_ground_diffuse'] = pvlib.irradiance.grounddiffuse(
            ghi=data['dirhi'] + data['dhi'],
github SunPower / pvfactors / pvfactors / timeseries.py View on Github external
# Reverse the surface normal to switch to back-surface circumsolar calc
    df_inputs_back_surface.loc[:, 'surface_azimuth'] = (
        df_inputs_back_surface.loc[:, 'surface_azimuth'] - 180.)
    df_inputs_back_surface.loc[:, 'surface_azimuth'] = np.mod(
        df_inputs_back_surface.loc[:, 'surface_azimuth'], 360.
    )
    df_inputs_back_surface.loc[:, 'surface_tilt'] = (
        180. - df_inputs_back_surface.surface_tilt)

    if df_inputs_back_surface.shape[0] > 0:
        # Use recursion to calculate circumsolar luminance for back surface
        df_inputs_back_surface = perez_diffuse_luminance(
            *breakup_df_inputs(df_inputs_back_surface))

    # Calculate Perez diffuse components
    components = irradiance.perez(df_inputs.surface_tilt,
                                  df_inputs.surface_azimuth,
                                  df_inputs.dhi, df_inputs.dni,
                                  dni_et,
                                  df_inputs.solar_zenith,
                                  df_inputs.solar_azimuth,
                                  am,
                                  return_components=True)

    # Calculate Perez view factors:
    a = aoi_projection(df_inputs.surface_tilt,
                       df_inputs.surface_azimuth, df_inputs.solar_zenith,
                       df_inputs.solar_azimuth)
    a = np.maximum(a, 0)
    b = cosd(df_inputs.solar_zenith)
    b = np.maximum(b, cosd(85))
github SunPower / pvfactors / pvfactors / irradiance / utils.py View on Github external
# Reverse the surface normal to switch to back-surface circumsolar calc
    df_inputs_back_surface.loc[:, 'surface_azimuth'] = (
        df_inputs_back_surface.loc[:, 'surface_azimuth'] - 180.)
    df_inputs_back_surface.loc[:, 'surface_azimuth'] = np.mod(
        df_inputs_back_surface.loc[:, 'surface_azimuth'], 360.
    )
    df_inputs_back_surface.loc[:, 'surface_tilt'] = (
        180. - df_inputs_back_surface.surface_tilt)

    if df_inputs_back_surface.shape[0] > 0:
        # Use recursion to calculate circumsolar luminance for back surface
        df_inputs_back_surface = perez_diffuse_luminance(
            *breakup_df_inputs(df_inputs_back_surface))

    # Calculate Perez diffuse components
    components = irradiance.perez(df_inputs.surface_tilt,
                                  df_inputs.surface_azimuth,
                                  df_inputs.dhi, df_inputs.dni,
                                  dni_et,
                                  df_inputs.solar_zenith,
                                  df_inputs.solar_azimuth,
                                  am,
                                  return_components=True)

    # Calculate Perez view factors:
    a = irradiance.aoi_projection(
        df_inputs.surface_tilt,
        df_inputs.surface_azimuth, df_inputs.solar_zenith,
        df_inputs.solar_azimuth)
    a = np.maximum(a, 0)
    b = cosd(df_inputs.solar_zenith)
    b = np.maximum(b, cosd(85))