pvdeg.humidity.back_encapsulant_water_concentration#

pvdeg.humidity.back_encapsulant_water_concentration(temp_module=None, rh_surface=None, rh_ambient=None, temp_ambient=None, start=None, Po_b=None, Ea_p_b=None, backsheet_thickness=None, So_e=None, Ea_s_e=None, back_encap_thickness=None, backsheet='W017', encapsulant='W001', output='rh')[source]#

Return water concentration in encapsulant.

Calculation is used in determining Relative Humidity of Backside Solar Module Encapsulant. This function returns a numpy array of the Concentration of water in the encapsulant at every time step.

This calculation uses a quasi-steady state approximation of the diffusion equation to calculate the concentration of water in the encapsulant. For this, it is assumed that the diffusion in the encapsulant is much larger than the diffusion in the backsheet, and it ignores the transients in the backsheet.

Numba was used to isolate recursion requiring a for loop Numba Functions are very fast because they compile and run in machine code but can not use pandas dataframes.

Parameters:

  • temp_module (pandas series (float)) – The surface temperature in Celsius of the solar panel module “module temperature [°C]”

  • rh_surface (list (float)) – The relative humidity of the surface of a solar module [%] EXAMPLE: “50 = 50% NOT 0.5 = 50%” if this parameter is not provided, it will be calculated using rh_ambient and temp_ambient.

  • rh_ambient (series (float)) – Ambient outdoor relative humidity. [%] Example: 50 = 50%, NOT 0.5 = 50% If rh_surface is not provided, this parameter along with temp_ambient will be used to calculate it.

  • temp_ambient (series (float)) – Ambient outdoor temperature [°C] If rh_surface is not provided, this parameter along with rh_ambient will be used to calculate it.

  • start (float) – Initial value of the Concentration of water in the encapsulant. by default, the function will use half the equilibrium value as the first value

  • Po_b (float) – Water permeation rate prefactor [g·mm/m²/day]. The suggested value for PET W17 is Po = 1319534666.90318 [g·mm/m²/day].

  • Ea_p_b (float) – Backsheet permeation activation energy [kJ/mol] . For PET backsheet W017, Ea_p_b=55.4064573018373 [kJ/mol]

  • backsheet_thickness (float) – Thickness of the backsheet [mm]. The suggested value for a PET backsheet_thickness=0.3.

  • So_e (float) – Encapsulant solubility prefactor in [g/cm³] So = 1.81390702[g/cm³] is the suggested value for EVA W001.

  • Ea_s_e (float) – Encapsulant solubility activation energy in [kJ/mol] Eas = 16.729[kJ/mol] is the suggested value for EVA W001.

  • back_encap_thickness (float) – Thickness of the backside encapsulant [mm]. The suggested value for EVA encapsulant is 0.46mm

  • backsheet (str) – This is the code number for the backsheet. The default is PET ‘W017’.

  • encapsulant (str) – This is the code number for the encapsulant. The default is EVA ‘W001’.

  • output (str) – The default is “rh” which is the relative humidity in the encapsulant in [%], any other value, e.g. “Ce” will return the concentration in [g/cm³].

Returns:

Ce_list (Pandas series (float)) – Concentration of water in the encapsulant at every time step in [g/cm³], or the relative humidity in [%] depending on the output parameter.