pvdeg.temperature.cell#

pvdeg.temperature.cell(weather_df: DataFrame, meta: dict, poa: DataFrame | Series = None, temp_model: str = 'sapm', conf: str = 'open_rack_glass_polymer', wind_factor: float = 0.33) → DataFrame[source]#

Calculate the PV cell temperature using pvlib-python.

Currently this only supports the SAPM temperature model.

Parameters:

  • weather_df ((pd.dataframe)) – Data Frame with minimum requirements of ‘temp_air’ and ‘wind_speed’

  • meta ((dict)) – Weather meta-data dictionary (location info)

  • poa ((dataframe or series, optional)) – Dataframe or series with minimum requirement of ‘poa_global’

  • temp_model ((str, optional)) – Specify which temperature model from pvlib to use. Current options: ‘sapm’

  • conf ((str)) –

    The configuration of the PV module architecture and mounting configuration. Options: ‘open_rack_glass_polymer’ (default), ‘open_rack_glass_glass’,

    ’close_mount_glass_glass’, ‘insulated_back_glass_polymer’

  • wind_factor (float, optional) – Wind speed correction exponent to account for different wind speed measurement heights between weather database (e.g. NSRDB) and the tempeature model (e.g. SAPM). The NSRDB provides calculations at 2 m (i.e module height) but SAPM uses a 10m height. It is recommended that a power-law relationship between height and wind speed of 0.33 be used*. This results in a wind speed that is 1.7 times higher. It is acknowledged that this can vary significantly.

  • Rabbani (R.)

  • Zeeshan (M.)

  • for ("Exploring the suitability of MERRA-2 reanalysis data)

  • estimation (wind energy)

  • potential (analysis of wind characteristics and energy)

  • Pakistan" (assessment for selected sites in)

  • 1240-1251. (Renewable Energy 154 (2020))

  • Return

  • -------

  • temp_cell (pandas.Series) – This is the temperature of the cell in a module at every time step.[°C]

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