Aerial Infrared Health Monitoring of Solar Photovoltaic Farms at Scale
Journal:
arXiv
Published Date:
Mar 3, 2025
Abstract
Solar photovoltaic (PV) farms represent a major source of global renewable
energy generation, yet their true operational efficiency often remains unknown
at scale. In this paper, we present a comprehensive, data-driven framework for
large-scale airborne infrared inspection of North American solar installations.
Leveraging high-resolution thermal imagery, we construct and curate a
geographically diverse dataset encompassing thousands of PV sites, enabling
machine learning-based detection and localization of defects that are not
detectable in the visible spectrum. Our pipeline integrates advanced image
processing, georeferencing, and airborne thermal infrared anomaly detection to
provide rigorous estimates of performance losses. We highlight practical
considerations in aerial data collection, annotation methodologies, and model
deployment across a wide range of environmental and operational conditions. Our
work delivers new insights into the reliability of large-scale solar assets and
serves as a foundation for ongoing research on performance trends, predictive
maintenance, and scalable analytics in the renewable energy sector.
