Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint

Kirsten Perry, Quyen Nguyen, Dirk Jordan, Chris Deline, Burton Putrah

Research output: Contribution to conferencePaper


In this research, we examine the relationship between aerial IR defect analysis and photovoltaic (PV) performance data for twelve utility- and commercial-scale solar sites in the United States. To do this, we fuse the site diagram geoJSON's, aerial infrared thermography (aIRT) defect analyses, and associated inverter time series, allowing for a direct comparison between site defects and time series data. Defect analyses were provided by Zeitview, under its Solar Insights platform. Following the data fusion process, we look at the relationship between system performance and aIRT defects. We investigate the relationship between degradation and hotspot defects, as well as the relationship between AC power data and offline strings and misaligned modules. In general, system degradation was not affected by long-term or balance-of-system (BoS) defects as they occurred infrequently in the data set. However, for one system, a near statistically significant relationship (p-value=0.057) was found when comparing the degradation of inverter blocks with several multi-hotspot defects to all other inverter blocks without this particular defect. There was strong alignment when comparing short-term recoverable module defects such as stuck trackers and offline strings to time series data. In general, we found that when an inverter block has more than 80% of modules flagged for one of these defects, its AC power time data is flat-lined and the inverter block is not producing.
Original languageAmerican English
Number of pages10
StatePublished - 2024
EventIEEE Photovoltaics Specialists Conference 52 - Seattle
Duration: 9 Jun 202414 Jun 2024


ConferenceIEEE Photovoltaics Specialists Conference 52

NREL Publication Number

  • NREL/CP-5K00-90316


  • aerial inspection
  • data fusion
  • degradation
  • hot spots
  • photovoltaics
  • time series


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