SUPERNOVA

• Polymer Competence Center Leoben GmbH (PCCL) (A)
• Accademia Europea di Bolzano (EURAC) (IT) - Coordinator
• Commissariat a l’Energie Atomique at aux Energie Alternatives (CEA) (FR)
• Fundacion Tecnalia Research & Innovation (Tecnalia) (ES)
• Universidad del Pais Vasco/Euskal Herriko Unibertsitatea (ES)
• UAB Soli Tek R&D (LT)
• Societe Industrielle de Construction d’Appareils et de Materiel Electriques (FR)
• Convert Italia S.p.a. (IT)
• 3E (BE)
• PVCASE UAB (LT)
• SAIDEA S.r.l. (IT)
• Statkraft AS (NO)
• Zelestra Corporacion SA (ES)
• BAYWA R.E. Operation Services S.r.l. (IT)
• BAYWA R.E. Energy Trading S.r.l. (IT)
• EPIA SolarPower Europe (BE)
• CSEM Centre Suisse d’Electronique at de Microtechnique SA Recherche et Development (CH)

SUPERNOVA addresses a key challenge in the rapidly expanding photovoltaic sector: ensuring reliable, efficient, and economically viable operation of large-scale solar power plants throughout their lifetime. As photovoltaic deployment accelerates across Europe and globally, solar installations are becoming increasingly complex infrastructures composed of thousands of interconnected components operating under highly variable environmental conditions. While module efficiencies and installation costs have improved significantly over the past decade, the operational phase of PV systems still presents major challenges related to monitoring, maintenance, data management, and long-term performance optimisation.

At the same time, the digitalisation of the energy sector has led to the generation of vast amounts of operational data from solar plants. Sensors, monitoring systems, meteorological data, and maintenance records continuously produce large datasets that could provide valuable insights into system performance and reliability. However, this information is often fragmented across different platforms and stakeholders, limiting its effective use. Without advanced analytics and interoperable tools, much of this data remains underexploited.

The SUPERNOVA project aims to unlock the value of these data streams by developing innovative digital solutions for the design, monitoring, and operation of solar PV plants. By combining advanced sensing technologies, artificial intelligence, robotics, and data-driven modelling, the project seeks to improve the reliability and efficiency of solar installations while reducing operation and maintenance costs. A key focus is the integration of large and heterogeneous datasets into interoperable digital platforms capable of transforming raw data into actionable insights for plant operators, asset managers, and technology developers.

• Improving the design of solar plants with data for increased performance, reliability, security, and flexibility
• Developing tools and components for different sensor technologies to be adaptable to different environments
• Using robotic solutions to reduce costs, increase data collection, and automate the process
• Using data fusion to generate insights and improve reliability via solar PV asset management software
• Developing methodology to classify solar components based on big data and artificial intelligence
• Increasing the profitability of solar PV systems via operation & maintenance (O&M), and grid-friendly strategies
• Creating confidence and business value in sharing solar PV data

SUPERNOVA integrates stakeholders across the entire PV value chain combining climate-specific plant design, digital twins, AI-driven analytics, and advanced O&M strategies, enabling more resilient solar plants, improved decision-making, and lower electricity costs through better project quality and performance over the system lifetime. SUPERNOVA’s methodology combines advanced monitoring, digitalisation, and AI-driven analytics to improve the design, operation, and long-term reliability of photovoltaic plants while enhancing sustainability and economic performance.

• Advanced sensing and diagnostics: Development of high-throughput, automated, and non-intrusive monitoring solutions capable of quantitatively linking degradation mechanisms with power loss, enabling early fault detection and predictive maintenance.
• Hybrid monitoring and robotics: Integration of complementary technologies such as drones, in-field robotics, and advanced inspection tools to automate failure detection, improve plant monitoring, and create detailed digital twins of PV installations.
• AI-driven data fusion and asset management: Use of interoperable digital platforms and language-based AI models to combine heterogeneous datasets, automate reporting and analysis, and support data-driven decision making for PV plant operators.
• Secure data spaces and sustainability integration: Establishment of FAIR data structures, federated learning frameworks, and privacy-preserving data sharing to enable collaborative model development while supporting circularity, reliability assessment, and long-term sustainability of PV systems. 

SUPERNOVA wird von der Europäischen Union kofinanziert (Grant Agreement ID 101084251). Die geäußerten Ansichten und Meinungen sind jedoch ausschließlich die der Autoren und spiegeln nicht unbedingt die der Europäischen Union oder der Exekutivagentur für Klima, Infrastruktur und Umwelt (CINEA) wider. Weder die Europäische Union noch die Förderbehörde können dafür haftbar gemacht werden.