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Third Trilateral Seed Fund between Siemens, TU Berlin and University of Oxford is bearing fruit

Four successful bids announced including Electricity Grid Modelling, Monitoring and Control for Distribution System Operators (DSOs)

Third Trilateral Seed Fund between Siemens, TU Berlin and University systems diagram

Four successful bids have been announced under the third Trilateral Seed Fund call of Siemens AG, Technical University of Berlin and the University of Oxford, following successful runs in 2020 and 2022.

Oxford e-Research Centre's Professor David Wallom is part of the the Electricity Grid Modelling, Monitoring and Control for Distribution System Operators (DSOs) bid.

The trilateral partnership between Siemens AG, TU Berlin, and the University of Oxford, builds upon the alliance between Berlin Universities and Oxford. Projects map onto call areas as shown in the diagram below, and will run during 2024 and are aimed at evolving partnerships for developing large-scale bids. 

The successful projects:

1. Electricity Grid Modelling, Monitoring and Control for Distribution System Operators (DSOs):   development of dynamic grid models for complex networks with increased penetration of distributed energy resources.  Implementation of AI-driven state estimation and control methods to improve security of supply.

Dr. Michael Metzger (Siemens), Prof. Jörg Raisch (TUB) & Profs. David Wallom & Alessandro Abate (University of Oxford), with Prof. Christian A. Hans (University of Kassel)

2. Towards a Unified Indoor Air Quality Management Framework: development of activity-based methodologies to quantify indoor air pollution. 

Dr. Martin Tackenberg (Siemens), Prof. Martin Kriegel (TUB) & Prof. Felix Leach (University of Oxford)

3. Calibration and Certification of Reduced Order Models (ROMs) for Fast and Reliable Digital Twins:  advancing the accuracy of Digital Twins throughout the physical twin's lifespan.

Dr. Dimitrios Loukrezis (Siemens), Dr. Karim Cherifi (TUB), Profs. Alessandro Abate & Ani Calinescu (University of Oxford)

4. ChatterDetect - Control-integrated AI Model for Chatter Detection: integrating Edge Computing and Machine Learning into manufacturing technology for efficient chatter detection in machine control systems.

Dr. Christine Funk & Daniel Regulin (Siemens), Martin Heper (TUB), Prof. Jack Umenberger (University of Oxford)

Previous Seed Fund projects have successfully developed large-scale projects: these include the €9.2m EU Horizon SMARTEDGE project.

Both University of Oxford and the Technical University of Berlin belong to the Siemens Research and Innovation Ecosystem, jointly addressing today’s challenges with future technologies in a collaborative way.

Contacts: Andy Gilchrist (University of Oxford), Ilaria Carrara Cagni (Siemens), Julia Guenther-Sorge (TUB)