Digital-Twin-Solar

The University of Kassel is involved with five other partners from science and industry in the joint project Digital-Twin-Solar. The project will receive funding from the Federal Ministry for Economic Affairs and Energy (BMWi) from May 2020 for three years.

The future network-connected components of the energy system allow extensive data acquisition to generate the digital twins of plants and power systems in digitalization. That means these plants and power systems should be accessible for optimization using machine learning (ML). The Digital Twin Solar project deals with solutions specially tailored to the use of solar energy and electricity storage systems. The overarching goal of the sub-project for the University of Kassel / Department IES is to develop the potential of the latest ML and artificial intelligence (AI) to develop digital twins' components in anomaly detection for PV and battery inverters. And at the same time to predict the time of the anomaly.

This research includes probabilistic forecasting, transfer learning, active learning, explainable AI, generative adversarial networks, and autoencoders. The project's goal is to develop further and adapt these ML methods and algorithms to unlock their potential for application in the renewable energy sector.