Probabilistic characterization of uncertainty in the photovoltaic cell modeling

In the paper the uncertainty of the photovoltaic (PV) cell model, by properly deriving the probability density function of the interest parameters, is characterized. This issue is crucial for predicting the capability of the photovoltaic source in producing electrical energy, but also for the control aspects of designing an efficient Maximum Power Point Tracker (MPPT). The PV source is modeled by means of a five parameters model: I_ph, I₀, V_T, R_s and R_sh. The probabilistic approach is based upon the knowledge of the cell datasheet. The shunt resistance R_sh, in absence of information, is characterized by a Gamma distribution. A statistical analysis, based upon Monte Carlo simulation, is performed for verify how the other parameters can be affected by the stochastic nature of the random variable. In the final part of the paper, the uncertainty of the datasheet values is also introduced. A case study is reported and the numerical results are discussed in detail.