4 citations · 4 across the 3 of their papers we have counts for
6 papers · 1 filter
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…
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…
On the Flow Problem in Water Distribution Networks: Uniqueness and Solvers
Manish K. Singh, Vassilis Kekatos
Increasing concerns on the security and quality of water distribution systems (WDS), call for computational tools with performance guarantees. To this end, this work revisits the p…
Optimal Distribution System Restoration with Microgrids and Distributed Generators
Manish Kumar Singh, Vassilis Kekatos, Chen-Ching Liu
Increasing emphasis on reliability and resiliency call for advanced distribution system restoration (DSR). The integration of grid sensors, remote controls, and distributed generat…
Natural Gas Flow Equations: Uniqueness and an MI-SOCP Solver
Manish K. Singh, Vassilis Kekatos
The critical role of gas fired-plants to compensate renewable generation has increased the operational variability in natural gas networks (GN). Towards developing more reliable an…
Optimal Scheduling of Water Distribution Systems
Manish K. Singh, Vassilis Kekatos
With dynamic electricity pricing, the operation of water distribution systems (WDS) is expected to become more variable. The pumps moving water from reservoirs to tanks and consume…