pvlib.pvarray.fit_pvefficiency_adr#

pvlib.pvarray.fit_pvefficiency_adr(effective_irradiance, temp_cell, eta, dict_output=True, **kwargs)[source]#

Determine the parameters of the ADR module efficiency model by non-linear least-squares fit to lab or field measurements.

Parameters

effective_irradiance (numeric, non-negative) – Effective irradiance incident on the PV module. [W/m^2]
temp_cell (numeric) – PV module operating temperature. [°C]
eta (numeric) – Efficiency of the PV module at the specified irradiance and temperature(s). [unitless] or [%]
dict_output (boolean, optional) – When True (default), return the result as a dictionary; when False, return the result as a numpy array.
kwargs – Optional keyword arguments passed to scipy.optimize.curve_fit. These kwargs can over-ride some options set within this function, which could be interesting for very advanced users.

Returns

popt (array or dict) – Optimal values for the parameters.

Notes

The best fits are obtained when the lab or field data include a wide range of both irradiance and temperature values. A minimal data set would consist of 6 operating points covering low, medium and high irradiance levels at two operating temperatures.