pvdeg.degradation.arrhenius_deg#

pvdeg.degradation.arrhenius_deg(weather_df, meta, rh_outdoor, I_chamber, rh_chamber, Ea, temp_chamber, poa=None, temp=None, p=0.5, n=1)[source]#

Calculate the Acceleration Factor between the rate of degredation of a modeled environmnet versus a modeled controlled environmnet. Example: “If the AF=25 then 1 year of Controlled Environment exposure is equal to 25 years in the field”

Parameters:
  • weather_df (pd.dataframe) – Dataframe containing at least dni, dhi, ghi, temperature, wind_speed

  • meta (dict) – Location meta-data containing at least latitude, longitude, altitude

  • rh_outdoor (float series) – Relative Humidity of material of interest Acceptable relative humiditys can be calculated from these functions: rh_backsheet(), rh_back_encap(), rh_front_encap(), rh_surface_outside()

  • I_chamber (float) – Irradiance of Controlled Condition [W/m²]

  • rh_chamber (float) – Relative Humidity of Controlled Condition [%]. EXAMPLE: “50 = 50% NOT .5 = 50%”

  • temp_chamber (float) – Reference temperature [°C] “Chamber Temperature”

  • Ea (float) – Degredation Activation Energy [kJ/mol] if Ea=0 is used there will be not dependence on temperature and degradation will proceed according to the amount of light and humidity.

  • poa (pd.dataframe, optional) – Global Plane of Array Irradiance [W/m²]

  • temp (pd.series, optional) – Solar module temperature or Cell temperature [°C]. If no cell temperature is given, it will be generated using the default parameters from pvdeg.temperature.cell

  • p (float) – Fit parameter When p=0 the dependence on light will be ignored and degradation will happen both day an night. As a caution or a feature, a very small value of p (e.g. p=0.0001) will provide very little degradation dependence on irradiance, but degradation will only be accounted for during daylight. i.e. averages will be computed over half of the time only.

  • n (float) – Fit parameter for relative humidity When n=0 the degradation rate will not be dependent on humidity.

Returns:

accelerationFactor (pandas series) – Degradation acceleration factor