Uncertainty Analysis for Maximum Power at SRC Using Hierarchical Monte Carlo Simulation

Mark Campanelli, Keith Emery, Ryan Elmore, Brian Zaharatos

Research output: Contribution to conferencePaperpeer-review

1 Scopus Citations


We present an uncertainty analysis (UA) for the maximum power of photovoltaic devices at standard reporting conditions, denoted Pmax0. The UA employs a hierarchical Monte Carlo (MC) simulation to sample from the state-of-knowledge probability distribution for Pmax0, based upon an irradiance and spectrally corrected current-voltage curve measured (nominally) at 1-sun according to ASTM E948-09 or E1036-12. A conditional factoring of the joint distribution of the parameters that determine Pmax0 allows rigorous consideration of both systematic (e.g., calibration chain) and random (e.g., solar simulator noise) sources of uncertainty in Pmax0. The corresponding hierarchical MC simulation is computationally efficient and parallelizable, allowing enough samples to control MC sampling error. The UA method complies with the Guide to the Expression of Uncertainty in Measurement.

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-5J00-61244


  • calibration
  • hierarchical modeling
  • maximum power
  • measurement uncertainty
  • Monte Carlo simulation
  • noise
  • uncertainty analysis


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