5 papers
ev-flow: A Reproducible, NHTS-Grounded Generator of Synthetic Plug-in Electric Vehicle Charging Behavior for Eight U.S. Regions
Bertrand Travacca
Electric-vehicle grid-integration studies need large, behaviorally realistic populations of individual charging profiles, but real charging telemetry is scarce and privacy-restrict…
Inducing Human Behavior to Alleviate Overstay at PEV Charging Station
Sangjae Bae, Teng Zeng, Bertrand Travacca +1
As the plug-in electric vehicle (PEV) market expands worldwide, PEV penetration has out-paced public PEV charging accessibility. In addition to charging infrastructure deployment,…
Implicit Deep Learning
Laurent El Ghaoui, Fangda Gu, Bertrand Travacca +2
Implicit deep learning prediction rules generalize the recursive rules of feedforward neural networks. Such rules are based on the solution of a fixed-point equation involving a si…
Hopfield Neural Network Flow: A Geometric Viewpoint
Abhishek Halder, Kenneth F. Caluya, Bertrand Travacca +1
We provide gradient flow interpretations for the continuous-time continuous-state Hopfield neural network (HNN). The ordinary and stochastic differential equations associated with…
Market based embedded Real Time Operation for Distributed Resources and Flexibility
Bertrand Travacca, Greg Rybka, Kenji Shiraishi
We build upon previous work out of UC Berkeley's energy, controls, and applications laboratory (eCal) that developed a model for price prediction of the energy day-ahead market (DA…