8 papers
Ripple-Type Control for Enhancing Resilience of Networked Physical Systems
Manish K. Singh, Guido Cavraro, Andrey Bernstein +1
Distributed control agents have been advocated as an effective means for improving the resiliency of our physical infrastructures under unexpected events. Purely local control has…
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…
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…
Online State Estimation for Time-Varying Systems
Guido Cavraro, Emiliano Dall'Anese, Joshua Comden +1
The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of…
An MILP Approach for Distribution Grid Topology Identification using Inverter Probing
Sina Taheri, Vassilis Kekatos, Guido Cavraro
Although knowing the feeder topology and line impedances is a prerequisite for solving any grid optimization task, utilities oftentimes have limited or outdated information on thei…
Graph Algorithms for Topology Identification using Power Grid Probing
Guido Cavraro, Vassilis Kekatos
To perform any meaningful optimization task, power distribution operators need to know the topology and line impedances of their electric networks. Nevertheless, distribution grids…