5 papers
Optimizing Energy Efficiency and Grid Stability via Public EV Charging Flexibility
Marek Miltner, Artem Bryksa, Ondřej Štogl +4
This study evaluates the potential of electric vehicle (EV) charging flexibility to enhance both energy efficiency and power grid stability. Using real-world data from public charg…
EasyRider: Mitigating Power Transients in Datacenter-Scale Training Workloads
Dillon Jensen, Obi Nnorom, Grant Wilkins +4
Large-scale AI model training workloads use thousands of GPUs operating in tightly synchronized loops. During synchronous communication, start-up, shut-down, and checkpointing, GPU…
From Servers to Sites: Compositional Power Trace Generation of LLM Inference for Infrastructure Planning
Grant Wilkins, Fiodar Kazhamiaka, Ram Rajagopal
Datacenter operators and electrical utilities rely on power traces at different spatiotemporal scales. Operators use fine-grained traces for provisioning, facility management, and…
Extending Load Forecasting from Zonal Aggregates to Individual Nodes for Transmission System Operators
Oskar Triebe, Fletcher Passow, Simon Wittner +9
The reliability of local power grid infrastructure is challenged by sustainable energy developments increasing electric load uncertainty. Transmission System Operators (TSOs) need…
Towards Using Machine Learning to Generatively Simulate EV Charging in Urban Areas
Marek Miltner, Jakub ZÃka, Daniel VaÅ¡ata +5
This study addresses the challenge of predicting electric vehicle (EV) charging profiles in urban locations with limited data. Utilizing a neural network architecture, we aim to un…