The expectations placed on PV technology are growing almost as fast as the industry itself. Investors are seeking consistently higher performances over longer lifetimes, and PV is increasingly being deployed in tropical regions, deserts and other harsh climate conditions.
While in many cases PV modules have shown that they can keep operating well beyond their warrantied lifetimes, a new report published by the European Technology and Innovation Platform Photovoltaics (ETIP PV) argues that more work is needed to ensure that PV systems are reliable in the long-term. Such research should also help increase bankability across the industry, potentially bringing costs down further.
The report, Research Challenges in PV Reliability, first recommends that the testing of PV modules go well beyond the current IEC specifications. Modules, according to ETIP PV, should be subject to multiple stress factors at once, and tests should relate directly to use cases. They also stress the need for collaboration and sharing of performance data from the field with the scientific community, particularly for newer technologies with little track record. “Accelerated degradation tests on component level need to walk hand-in-hand with performance assessment under relevant climatic conditions, and system-level testing,” the report states. “Soiling, salinity, humidity, high temperatures, and high UV exposure may affect different technologies in different ways and accelerate module degradation.”
The report further notes that as PV becomes more integrated with other technologies, and use cases move beyond traditional ground mount or rooftop applications, testing needs to move with the times and ensure all use cases are counted for. “As an example, vehicle, noise barrier and road integration environment subject modules to severe levels of dynamic mechanical stress, while floating PV exposes modules and BOS components to high levels of humidity,” the authors explain. “Reliability Research needs to investigate the associated material stress and to design and validate adequate accelerated test procedures.”
Beyond ensuring that individual components are up to the task they have been set, there are also challenges in system design, particularly related to the use of new technologies and reduction of uncertainty in yield predictions.
And the report outlines a crucial role for operations and maintenance providers and the new technologies at their disposal – such as infrared imaging using drones along with other sensors and inspection technologies – to collect performance that can be fed into machine learning algorithms. This could both reduce downtime at a particular site and identify problems that could be addressed more easily earlier on in the process. “Artificial Intelligence techniques, such as machine learning, have started to be applied to the huge amount of monitoring data already available… with immediate positive impacts on plant downtime and availability,” states the report. “Nevertheless, more powerful on-site and in-situ characterization tools and techniques as well as remote automatic failure detection supported by AI are necessary.”
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