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08:30 - 10:10
EMOB SESSION 3B – AI / MACHINE LEARNING FOR GRID INTEGRATION
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Room: Douro III
08:30 - 08:50
01 GIW26-323
Benchmarking Large Language Models for Electric Vehicle Charging Session Forecasting
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José Andrade, INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Portugal
08:50 - 09:10
02 GIW26-313
Transfer learning-based utilization forecasting for fleets of EV charging stations
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Sebastian Schreck, Siemens AG, Germany
09:10 - 09:30
03 GIW26-166
Preference-Conditioned Multi-Agent Reinforcement Learning for Real-Time EV Charging Coordination Under Grid Constraints
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Syed Irtaza Haider, Deutsche Telekom Chair of Communication Networks, TUD Dresden University of Technology, Dresden, Germany, Germany
09:30 - 09:50
04 GIW26-70
AI-Based Prediction of Battery Charging Behaviour in a PV–Wind Hybrid System for EV Charging Applications
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oluchi ugbe, Competence Center for Renewable Energies and Energy Efficiency (CC4E), Germany | Africa Center of Excellence for Sustainable Power and Energy Development (ACE-SPED), Nigeria
09:50 - 10:10
OPEN FLOOR / DISCUSSION