5 citations · 9 across the 8 of their papers we have counts for
18 papers
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation
Shuhang Chen, Adithya Devraj, Andrey Bernstein +1
The ODE method has been a workhorse for algorithm design and analysis since the introduction of the stochastic approximation. It is now understood that convergence theory amounts t…
Novel Region of Attraction Characterization for Control and Stabilization of Voltage Dynamics
Bai Cui, Ahmed Zamzam, Guido Cavraro +1
In this paper, we study the monitoring and control of long-term voltage stability considering load tap-changer (LTC) dynamics. We show that under generic conditions, the LTC dynami…
Grid-forming frequency shaping control
Yan Jiang, Andrey Bernstein, Petr Vorobev +1
As power systems transit to a state of high renewable penetration, little or no presence of synchronous generators makes the prerequisite of well-regulated frequency for grid-follo…
Learning to Optimize Power Distribution Grids using Sensitivity-Informed Deep Neural Networks
Manish K. Singh, Sarthak Gupta, Vassilis Kekatos +2
Deep learning for distribution grid optimization can be advocated as a promising solution for near-optimal yet timely inverter dispatch. The principle is to train a deep neural net…
Model-Free State Estimation Using Low-Rank Canonical Polyadic Decomposition
Ahmed S. Zamzam, Yajing Liu, Andrey Bernstein
As electric grids experience high penetration levels of renewable generation, fundamental changes are required to address real-time situational awareness. This paper uses unique tr…
A Framework for Distributed and Compositional Stability Analysis of Power Grids
Stefanos Baros, Andrey Bernstein, Nikos Hatziargyriou
Operating modern power grids with stability guarantees is admittedly imperative. Classic stability methods are not well-suited for these dynamic systems as they involve centralized…