Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data

Brian Zaharatos, Mark Campanelli, Clifford Hansen, Keith Emery, Luis Tenorio

Research output: Contribution to conferencePaperpeer-review

3 Scopus Citations


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.

Original languageAmerican English
Number of pages6
StatePublished - 15 Oct 2014
Event40th IEEE Photovoltaic Specialist Conference, PVSC 2014 - Denver, United States
Duration: 8 Jun 201413 Jun 2014


Conference40th IEEE Photovoltaic Specialist Conference, PVSC 2014
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

NREL Publication Number

  • NREL/CP-5J00-61245


  • likelihood function
  • maximum likelihood estimator
  • noise model
  • parameter estimation
  • single-diode model


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