Event Programme 2026
Sunday 13 September 2026
Rotterdam, The Netherlands
On the occasion of the EU PVSEC 2026, 43rd European Photovoltaic Solar Energy Conference and Exhibition.
WTC World Trade Center
Beursplein 37
3011 AM Rotterdam

9:00–11:30
Space Photovoltaics from Lab to Launch

Description
This 2.5-hour tutorial provides a practical, PV-specific introduction to using artificial intelligence across R&D, manufacturing, field operations, and grid integration. Through concrete use cases—including experimental design, defect and failure analysis, yield improvement, performance monitoring, production forecasting, and congestion management—the session will show where AI can add value, where caution is needed, and how human expertise can be combined with machine intelligence to learn faster and improve outcomes. Participants will also learn practical workflows for building bespoke AI tools with frontier models, including data structuring, prompting, validation, and expert review. A hands-on activity will help participants apply these concepts to a representative PV problem.
13:00–15:30
AI for PV: Tools & Examples Across the Value Chain and Product Life Cycle
16:00–18:30
PV and BESS Integration into the Grid
9:00–11:30
Space photovoltaics from Lab to Launch
As the global space sector undergoes a radical transformation, the demand for innovative, high-performance power solutions has never been more critical. This lecture class considers the evolution of space photovoltaic systems and how emerging applications are driving innovation.
This lecture class covers:
- Unique features of the space environment requiring custom PV solutions: AM0 spectrum, plasma and atomic oxygen, thermal cycling and particle radiation.
- Radiation induced degradation: Damage mechanisms, simulation methods and correlation with ground-based testing, along with the role of shielding.
- Key design features of current space photovoltaic solutions, powering payloads delivering critical space-based services today and their qualification standards.
- Emerging applications and evolving design criteria. Next generation satellite networks; high power space infrastructure; space exploration and science in space placing new demands on the PV power systems including: lower cost, high specific power, on-orbit assembly compatibility and extended duration survival in hostile space environments.
- Novel space PV concepts: potential advantages and challenges.
This lecture class would be useful for researchers from all career stages looking to understand specific challenges associated with photovoltaics in space environments, tool kits and methodologies for modelling these effects and correlating with prospective mission profiles, current state-of-the-art space power solutions and how they are qualified, and how the demands of emerging applications are driving innovation in this field. The course has been developed as an academic/industrial collaboration and would suit attendees interested in the challenges of translating novel device designs and alternative material platforms to scalable space photovoltaics technology solutions.
13:00–15:30
AI for PV: Tools & Examples Across the Value Chain and Product Life Cycle
Artificial intelligence is rapidly becoming relevant to photovoltaics, but its most valuable uses are often application-specific and require careful integration with domain expertise. This 2.5-hour tutorial will provide a practical introduction to how AI can support the PV innovation and deployment lifecycle, from research and development to manufacturing, field operations, and grid integration. The emphasis will be on actionable workflows rather than general AI theory, with examples chosen to reflect real challenges in PV research and industry.
The tutorial will cover concrete use cases including experimental design, defect and failure analysis, manufacturing-variance reduction, performance monitoring, production forecasting, and congestion management. These examples will illustrate where AI can accelerate learning, reveal patterns in complex data, and support decision-making under uncertainty. They will also highlight important limitations, including data quality, low-data regimes, model validation, interpretability, and the risks of over-reliance on automated outputs.
Participants will learn practical workflows for building bespoke AI tools with frontier models, including how to structure data, design prompts, check outputs, integrate expert review, and keep humans in the loop. The session will conclude with a hands-on activity in which participants apply these concepts to a representative PV problem. Attendees will leave with a clearer understanding of where AI is useful in PV today, where caution is required, and how to design AI workflows that improve learning speed & quality in PV research & industrial practice.