Utility-scale solar facility operators spend thousands of labor hours inspecting, identifying and isolating faulty, dirty or shaded solar panels. This operation and maintenance (O&M) challenge is costly and impacts the competitiveness of solar energy pricing. As the US solar industry continues to grow in US markets driven by renewable portfolio standards, large-scale solar facilities will become more common and will be forced to optimize their O&M budgets in order to compete. Through small, unmanned aerial vehicles (sUAS), solar facility operators can obtain low-cost, real-time inspection data, geospatially organized, and coupled with an asset tracking user platform. Flying multi-rotor sUASs, pre-programmed with geospatial information systems (GIS) waypoints in an automated flight pattern over solar fields allow capture of both visual and infrared spectrum data, identifying hot cells, glass cracks, shading, etc. Such a system produces actionable geospatial data, enabling operators to substantially reduce labor hours spent inspecting whole solar fields and instead target deficient panels only. Few, if any, sUAS developers have demonstrated the capability to package reliable sUAS automation with data processing and an intuitive graphical user interface for this application. A simple, robust, low-cost solution is necessary that requires minimal technical training to deploy the sUAS and interpret its findings.
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