Likelihood methods for single-diode model parameter estimation from noisy I–V curve data

Characterizing photovoltaic (PV) device performance is important for the growth of the PV industry. Performance is often characterized by a set of key parameters for the PV device in question: open-circuit voltage, short-circuit current, and maximum power. For a wide range of devices, the key performance parameters are a function of the parameters of a single-diode circuit model. In this paper, we present a statistical model for current-voltage-irradiance data of a PV device using a five-parameter single-diode model. The goal is to estimate the single-diode model parameters and key performance parameters with quantified uncertainty. Specifically, we find maximum likelihood estimates, quantify uncertainty via confidence intervals for the model and key performance parameters, and explore two important statistical properties of this model-identifiability and estimability.