Recording from Tuesday, February 17, 2026 | Solar Quality Summit | Language: English | Duration: 67:32 .
What if you could spot PV performance issues before they impact energy yield — and act on them immediately?
Led by the SUPERNOVA project, this session is a live-data showcase of next-generation tools that are redefining predictive maintenance in solar O&M. Rather than focusing on theory, the session demonstrates how advanced monitoring concepts work in practice and how they translate into faster, more informed operational decisions. A key enabler of predictive maintenance is the systematic collection, structuring, and integration of data within dedicated digital platforms. By aggregating diverse data streams, these platforms ensure that information is consistent, accessible, and ready for advanced analytics. The session highlights novel data sources that unlock truly predictive capabilities, including early-stage material degradation detection using near-infrared spectroscopy, environmental sensors on trackers enabling automated weather-triggered safety actions, and innovative I–V curve estimation approaches based on string-level and non-intrusive module-level monitoring. Attendees will gain insight into how these technologies perform in real operational environments and how high-quality, well-organised data directly supports the development and validation of predictive models — ultimately improving plant reliability, reducing downtime, and increasing operational efficiency.
Moderation
Lukas Koester
Researcher
EURAC
Speaker
Will Hitchcock
Founder and CEO
Above
Dr. Chiara Barretta
Researcher
Sustainable Polymer Solutions
PCCL
Andrea Monni
Program, Quality and Process Manager
Convert Italia
Ricardo Alonso
Manager of Renewable Energy O&M Platform
Tecnalia Research & Innovation