Dr. A. (Angela) Meyer

Profile

I have been an assistant professor of energy meteorology and artificial intelligence at TU Delft since October 2023. I obtained my PhD in atmospheric physics from ETH Zurich and a master’s degree in mathematics from the University of Cambridge. I also gained industry experience as a data scientist at Hexagon AB and co-leader of a R&D program at Siemens Smart Infrastructure.

Research

My research interests lie at the intersection of data science, atmospheric science and energy applications. Since 2022, I have been leading a research group in machine learning and renewable energy applications at Bern University of Applied Sciences. Research in my group is supported by the Swiss National Science Foundation and the Innovation Agency Innosuisse.

Key publications

Carpentieri, A., D. Folini, J. Leinonen, A. Meyer, 2024, Extending intraday solar forecast horizons with deep generative models, Applied Energy, doi:10.1016/j.apenergy.2024.124186
Grataloup, A., S. Jonas, A. Meyer, 2024, A review of federated learning in renewable energy applications: Potential, challenges, and future directions, Energy and AI, 17, doi:10.1016/j.egyai.2024.100375
Carpentieri, A., S. Pulkkinen, D. Nerini, D. Folini, M. Wild, A. Meyer (2023), Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection, Applied Energy, 351, doi:10.1016/j.apenergy.2023.121775
Carpentieri, A., D. Folini, M. Wild, L. Vuilleumier, A. Meyer (2023), Satellite-derived solar radiation for intra-hour and intra-day applications: Biases and uncertainties by season and altitude, Solar Energy, 255, 274-284, doi:10.1016/j.solener.2023.03.027
Meyer, A. (2021), Multi-target normal behaviour models for wind farm condition monitoring, Applied Energy, doi:10.1016/j.apenergy.2021.117342
Kuhn, P., S. Wilbert, C. Prahl, D. Schüler, T. Haase, T. Hirsch, M. Wittmann, L. Ramirez, L. Zarzalejo, A. Meyer, L. Vuilleumier, P. Blanc, R. Pitz-Paal (2017), Shadow camera system for the generation of solar irradiance maps, Solar Energy, doi: 10.1016/j.solener.2017.05.074