A Method for Estimating Time-Series PV Production Loss From Solar Tracking Failures

Kevin Anderson, Christopher Downs, Saurabh Aneja, Matthew Muller

Research output: Contribution to journalArticlepeer-review

1 Scopus Citations


Solar tracking system failures can dramatically reduce photovoltaic (PV) system energy output through suboptimal irradiance capture and self-shading loss. Detecting tracker failures is not always straightforward; unlike other common PV system failures like inverter outages and blown fuses which take portions of a system completely offline, tracker failures only partially reduce output power and can go unnoticed as a result. Additionally, tracker failures can take one of several forms, each with their own loss characteristics. Here we present two methods of detecting tracker failure events from time-series production data and a method for estimating the associated production loss. Compared with existing detection methods, the proposed power-based detection method showed 0-17% reductions in Type I error rate depending on weather conditions. The loss model estimated production loss with low error (mean bias error = -2.3%, root-mean-squared error = 6%) in a rudimentary validation.

Original languageAmerican English
Pages (from-to)119-126
Number of pages8
JournalIEEE Journal of Photovoltaics
Issue number1
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2011-2012 IEEE.

NREL Publication Number

  • NREL/JA-5K00-80280


  • Backtracking
  • Failure
  • Photovoltaic
  • Shading
  • Single-axis tracking
  • Stall


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