Leveraging Drones for PV Plant Inspections: Page 2 of 3
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What Can Drones Detect?
Aerial thermography provides site-wide coverage for utility-scale and C&I solar installations. According to Randall Warnas, segment leader for global small unmanned aerial systems (sUASs) at FLIR, the world’s largest IR camera manufacturer, “Handheld thermal cameras are an industry standard for inspecting PV systems, and drones put that technology in the air. By the numbers, solar has been one of the top applications for thermal drones, second only to law enforcement and emergency services.”
In PV applications, drones equipped with infrared and visible RGB cameras can detect module-specific issues such as activated bypass diodes, production batch issues, junction box heating, and cell and multicell defects including cracking. Technicians can also use aerial thermography to identify and document electrical equipment and system-scale issues such as PV array source-circuit failures, reversed polarity, and array combiner box and inverter failures. Aerial site inspections can identify site issues such as shading from new vegetative growth, excessive soiling, tracker failure and security breaches.
Drone inspections can generate hundreds or thousands of images per site. However, the consistent geometry of PV systems allows for the separation of modules and the use of artificial intelligence to diagnose module defects, while simultaneously assessing and comparing the hierarchy of subsystems such as module versus module or string versus string.
Make Drone Data Actionable
To optimize time savings, you should match drone data capture to the specific management goal, such as identification of off-line PV source circuits or module-level cell defects. No matter how much drone data you collect, proper PV system analytics deliverables should provide four primary components:
A high-level overview. Data should enable a technician to prioritize repairs in a limited time window. Deliverables should specifically call out, in an executive summary, large defects, such as an inverter or combiner failure, and their impact on the plant’s overall capacity and production. This summary allows supervisors to triage sites under their management.
Granularity. Results should associate every identified defect with an image, location, classification and affected dc system capacity; give summary statistics for each subarray or array; and allow you to filter results by location and defect category. Technicians can refer back to these results when tracking site conditions over time.
Location. Inspection analytics deliverables should provide defect locations using a localized coordinate system, such as subarray, row, string and module number, as well as GPS locations. GPS identifiers help analysts visualize the distribution of issues, while localized coordinates are more useful for field technicians replacing modules. You can base localized coordinates on a geographic location, such as the number of rows north, or on the asset designations in the as-built drawings.
Compatible results. Finally, analysis and report deliverables should come in an open format, such as a spreadsheet or KML file, that the client can easily import into a variety of software systems. As drone-based thermography, analysis and reporting technology become more widely deployed, that sets the stage for an open data standard that allows asset owners and O&M companies to track site progression regardless of who collected the data. Given the multitude of solar monitoring and aggregation software platforms, an open data standard will also make it possible to reduce software integration complexity.