Smart Algorithms to Detect Issues in Rooftop Solar Panels

At the University of New South Wales and the University of Technology Sydney, researchers have crafted innovative algorithms designed to identify various issues that decrease solar panel efficiency, such as wiring problems, degradation, and shading.

Senior Lecturer Fiacre Rougieux from the UNSW School of Photovoltaic and Renewable Energy Engineering emphasized that this technology could significantly advance fault diagnosis in PV systems. He highlighted its ability to detect problems like clipping, tripping, and export limits, calling it a transformative development for those managing residential and commercial solar systems in Australia.

“Utilizing data from inverters and power points every five minutes, our algorithm precisely pinpoints performance issues, facilitating prompt rectification and enhancing energy output,” Rougieux explained.

The development is part of a NSW Smart Sensing Network project. The team has introduced a dual-level diagnostic method employing sensors and varied analytical techniques. This method addresses solar panel inefficiencies, which are responsible for estimated annual global losses of around AUD 7 billion ($4.6 billion) due to preventable issues.

Rougieux described their pioneering approach, which utilizes AC power data to broadly identify issues such as complete loss of generation and system tripping. This method is particularly versatile, compatible with any inverter or power point tracking system.

Additionally, the researchers have devised a more nuanced algorithm that incorporates both AC and DC data. This allows for a more detailed examination and categorization of specific problems like shading and connection issues in solar panel strings. Rougieux noted that this sophisticated diagnostic tool combines statistical rules and machine learning to tackle cases that elude traditional methods.

The newly developed technology has been successfully incorporated into a commercial platform currently utilized by Global Sustainable Energy Solutions to oversee over 100 MW of solar installations. This integration has taken place across more than 1,200 PV systems, according to UTS team leader Ibrahim Ibrahim.

Ibrahim highlighted the significant impact of this technology, noting that it has fostered proactive management strategies that not only maximize energy production but also boost the overall reliability of the systems. "This technological advance cuts down the preventable losses valued in billions on a global scale, translating into considerable savings for owners of photovoltaic systems," he stated.

Fiacre Rougieux further explained the practical benefits of the software, particularly in reducing the reliance on costly on-site contractors for diagnosing performance issues. He recounted an instance where a local council's solar system had been underperforming for five months without detection under a maintenance contract. "Our algorithms identified the problem almost immediately, revealing the extensive number of undetected issues in systems maintained by contractors," Rougieux revealed.

The team is actively working to refine these algorithms further. Their goal is to expand the technology’s diagnostic capabilities to include a wider array of issues like shading, soiling, and intricate grid-side faults, thus broadening the scope and effectiveness of their solution.

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