IPVF offers advanced reliability testing coupled with AI-driven modelling to predict PV degradation, forecast energy yield, and improve device stability. The service integrates multi-technique characterization (imaging, KP, luminescence, IV diagnostics, energy yield assessment) with AI models to build a digital twin for real-time monitoring, failure detection, and explainable degradation forecasting.
Virtual Access
Combines reliability testing with AI-driven modelling to predict degradation and improve energy-yield forecasting for next-gen PV
- Covers: performance/degradation analysis, AI-based characterization, digital twins, real-time data analysis, multi-technique imaging, IV diagnostics, energy yield, failure detection, and explainable forecasting
- Facility Capabilities
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- Multi-technique characterization: imaging (KP, luminescence), IV diagnostics, energy yield assessment
- AI models couple characterization data with predictive analysis to build a digital twin for real-time monitoring and diagnostics
- Supports failure detection and degradation forecasting, with focus on explainability and traceability