Preprocessing uncertain photovoltaic data

Miao Fan, Vijay Vittal, Gerald T. Heydt, Raja Ayyanar

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


This letter suggests a method to manage the uncertainty of photovoltaic (PV) data by removing the periodic effect of the annual position of the sun in the sky. The least squares method is applied to determine the low-frequency (annual) periodic component which is predictable in the system operation. This method can be applied to estimate the probabilistic characteristics of PV generation at various locations on the earth with differing insolation due to changing solar position.

Original languageEnglish (US)
Article number6677516
Pages (from-to)351-352
Number of pages2
JournalIEEE Transactions on Sustainable Energy
Issue number1
StatePublished - Jan 2014


  • Least squares method
  • Photovoltaic (PV) generation
  • Probability density function (pdf)
  • Renewable energy
  • Uncertainty

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment


Dive into the research topics of 'Preprocessing uncertain photovoltaic data'. Together they form a unique fingerprint.

Cite this