Solar Quality Summit Europe 2026

Framing AI and robotics as solutions but prompting an honest exploration of what they can and cannot solve. AI and robotics are increasingly promoted as the next frontier for quality assurance in solar but how far can they really take us? This session takes a critical, grounded look at where AI is delivering meaningful improvements in PV system quality and where its limitations still require human expertise, better data, or a shift in approach.

From fault detection and predictive maintenance to automated inspections and performance forecasting, AI has already transformed parts of the PV lifecycle. But not all quality issues can be solved by algorithms. Incomplete datasets, misclassified failures, and emerging technologies with no historical field data challenge the current capabilities of even the most advanced AI systems.

As PV and storage systems become increasingly connected, they are also more exposed to cyber threats. This session examines the most pressing vulnerabilities in inverters, SCADA networks, and BESS controllers. From anomaly detection to secure-by-design architectures, we’ll show how the industry is staying ahead of attacks that could compromise performance and revenue. Real examples will highlight what works when prevention is the priority.

AI and robotics are not replacing technicians - they are making their jobs safer and more effective. This session looks at how drones, autonomous cleaners, and remote monitoring reduce time spent in hazardous conditions while delivering richer, more precise data. Attendees will see how shifting physical risk to machines frees human talent for analysis, optimization, and complex problem-solving. Real-world examples show how this human-machine collaboration is raising both safety and operational quality.

As next-generation PV technologies like TOPCon and bifacial modules enter the field, traditional AI forecasting faces a critical challenge: past performance no longer reliably predicts future outcomes. This session explores how these advanced modules can behave differently in real-world conditions compared to lab results, revealing the limits of historical datasets. Attendees will learn strategies for capturing early field insights, understanding when AI predictions may falter, and leveraging expert oversight to complement machine learning. The result: a smarter, more adaptive approach that integrates human judgment and AI to guide evolving solar technologies.

Explore how AI agents can enhance PV plant monitoring with insights from the SUPERNOVA project through a mix of presentations and hands-on group exercises. 

Participants will design and test simple AI agents for alarm analysis or decision support in a simulated environment. The session concludes with a discussion on integrating intelligent automation into real-world plant operations.

*This is a closed workshop with a limited number of attendees, on a first-come first-served basis. 
If you're interested in participating please send an email to b.fernandez[at]solarpowereurope.org for the registration form.

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.

Blackouts show how a single point of failure in critical infrastructure can cascade across systems and cause widespread disruption. Modern PV plants are part of this same interconnected ecosystems, where one compromised asset can trigger far-reaching consequences. During this interactive session, together we will explore how to prepare for cascading risks and what solutions are available today to strengthen resilience.

Transform scattered technical documentation into automated operational decisions in this hands-on session. 

We'll demonstrate the complete journey: AI extracts critical insights from your reports, contractual documentation, and maintenance manuals, then you'll learn to operationalize that intelligence - auto-generating work orders, triggering warranty claims, scheduling interventions, and maintaining asset compliance. Using real solar plant scenarios, you'll see documents become structured data, data become validated insights, and insights become executed actions with clear ownership and timing. Walk away with a proven framework to eliminate manual reconciliation, reduce errors, and scale your technical operations without scaling headcount.

*This is a closed workshop with a limited number of attendees, on a first-come first-served basis. 
If you're interested in participating please send an email to b.fernandez[at]solarpowereurope.org for the registration form.

Long-term reliability isn’t just an engineering goal – its a financial strategy. This flagship session presents findings from the 2026 PV + Storage Technical Due Diligence Report, revealing how risk prediction, smart component selection, and advanced modeling are making projects more financeable.

Following the Summit programme, the Networking Dinner offers great opportunities to connect and exchange gathered insights while enjoying a panoramic view over Barcelona (more details on the Networking Dinner page).

Reliability is won or lost in the details. Not all failures make headlines but many of them quietly erode performance, increase maintenance costs, and compromise long-term plant reliability. From cracked connectors and loose terminations to degraded junction boxes and premature tracker failures, small component-level issues can have big operational consequences. This session zooms in on the often-overlooked failures that accumulate over time, and what it takes to prevent them through better component design, selection, and system engineering. 

In light of recent cybersecurity regulations impacting the solar industry, including landmark regulatory, legislaive acts such as NIS2, CRA, NCCS and possible restrictions on supply chains and sourcing of key components such as inverters, this session will deal with efficient, cost-effective and timely methods of ensuring compliance while continuing to rely on global supply chains.

Advances in artificial intelligence are transforming how the solar industry predicts weather, generation, and grid behavior. This session brings together leading research and applied innovations, with a spotlight on recent advances in the Supernova project. We will review the latest model developments from Google, NVIDIA, and the European Centre for Medium-Range Weather Forecasts (ECMWF) and examine how these breakthroughs are reshaping short- and medium-term weather forecasting. The session will also feature: AI models for day-ahead irradiance forecasting, Ensemble models for probabilistic PV forecasting, Net load forecasting at the primary substation level (preliminary results), Day-ahead congestion forecasting for interzonal transmission lines (preliminary results).

Attendees will leave with insights into how cutting-edge AI models and the Supernova project are enhancing forecast accuracy, reducing uncertainty, and enabling more resilient solar and grid operations.

Extreme weather events: storms, heatwaves, hail, and high winds pose growing risks to PV plants. This session explores technical solutions to make systems more resilient, including structural reinforcement, advanced mounting designs, robust electrical layouts, and protective component choices. AI tools for predictive modeling and stress simulation will be highlighted as complementary methods to validate and optimize these engineering solutions. Attendees will gain actionable insights on designing PV systems that maintain performance and reliability under severe environmental conditions.

As solar and storage systems mature, every upgrade decision – whether re-sizing through revamping, integrating BESS, or replacing core components – carries significant financial and technical consequences. This session shows how targeted interventions can transform legacy assets into high-performing, future-ready power plants. Through real-world case studies, participants will see how to diagnose system bottlenecks, prioritize upgrades that deliver the greatest return, and integrate new solutions – such as advanced inverters, trackers, storage, or re-sized plant layouts – without compromising existing performance. Emphasis on the human+analytics collaboration demonstrates how expert judgment complements operational data, providing actionable frameworks to maximize energy yield, extend asset life, and strengthen bankability. 

Attendees will leave with practical strategies to turn aging portfolios into resilient, high-value assets – ensuring that every retrofit delivers measurable, lasting impact.

Even with advanced technology, many PV plants still underdeliver on expected energy yield for years before root causes are identified. This session dissects real-world cases of chronic underperformance to uncover the technical, operational, and environmental drivers that suppress production. We will highlight how AI and robotics can accelerate performance diagnostics – while also showing their limits when data quality is weak or problems are novel. Attendees will leave with a sharper framework for diagnosing lost yield and restoring production quickly and sustainably.

Digital twins are transforming how PV projects are delivered, providing a real-time virtual replica of the site where drones, sensors, and automated analysis converge. This session shows how deviations from design can be flagged and corrected immediately, ensuring as-built quality aligns with specifications and long-term performance targets.
Attendees will see field-tested workflows for integrating digital twins with construction oversight, predictive maintenance planning, and commissioning, demonstrating measurable gains in energy yield, rework reduction, and reliability. The session emphasizes how AI-driven insights complement experienced engineering judgment, giving teams the tools to manage complex PV projects with precision and confidence.

The battery market is racing toward larger, denser cells to reduce upfront project costs, but “bigger” isn’t always better for long-term reliability. As cell size increases, managing internal heat and mechanical stress becomes exponentially more complex, which can silently accelerate degradation and shorten system life. This discussion will explore the trade-offs between immediate cost savings and 20-year durability, helping attendees identify which technologies truly support a profitable total cost of ownership.

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