4 citations · 6 across the 7 of their papers we have counts for
10 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…
Learning to Solve the AC-OPF using Sensitivity-Informed Deep Neural Networks
Manish K. Singh, Vassilis Kekatos, Georgios B. Giannakis
To shift the computational burden from real-time to offline in delay-critical power systems applications, recent works entertain the idea of using a deep neural network (DNN) to pr…
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…
Moving horizon-based optimal scheduling of EV charging: A power system-cognizant approach
Nitasha Sahani, Manish Kumar Singh, Chen-Ching Liu
The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable…
Joint Grid Topology Reconfiguration and Design of Watt-VAR Curves for DERs
Manish K. Singh, Sina Taheri, Vassilis Kekatos +2
Operators can now remotely control switches and update the control settings for voltage regulators and distributed energy resources (DERs), thus unleashing the network reconfigurat…
Natural Gas Flow Solvers using Convex Relaxation
Manish Kumar Singh, Vassilis Kekatos
The vast infrastructure development, gas flow dynamics, and complex interdependence of gas with electric power networks call for advanced computational tools. Solving the equations…