1 citations · 1 across the 6 of their papers we have counts for
7 papers
Optimal Control of Dynamic Gas Networks Using Gaussian Processes with Chance-Constraint Reformulation
Taiwo A. Adebiyi, Robert Ferrando, Manuel Garcia +3
Natural gas networks must accommodate variable demand and supply while maintaining pressure across pipelines whose stored gas couples operating decisions through time. Probabilisti…
Efficient Graph Partitioning under Resource Constraints: A Cutting-Plane Framework for Distribution Grids
Duong Thuy Anh Nguyen, Harsha Nagarajan, Robert Ferrando +2
This paper presents an optimal network topology control framework using cutting-plane methods for efficient network partitioning with controllable edges. The objective is to enable…
Load Block Modeling in Distribution Systems: Network Reconfiguration for Load Restoration
David M. Fobes, Harsha Nagarajan, Manuel Garcia +2
The distribution system restoration (DSR) problem has received considerable attention over the last decade or more. Solutions to the DSR problem identify the best set or sequence o…
System-Wide Emergency Policy for Transitioning from Main to Secondary Fuel
Laurent Pagnier, Criston Hyett, Robert Ferrando +4
Faced with the complexities of managing natural gas-dependent power system amid the surge of renewable integration and load unpredictability, this study explores strategies for nav…
Differentiable Simulator For Dynamic & Stochastic Optimal Gas & Power Flows
Criston Hyett, Laurent Pagnier, Jean Alisse +4
In many power systems, particularly those isolated from larger intercontinental grids, operational dependence on natural gas becomes pivotal, especially during fluctuations or unav…
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study
Robert Ferrando, Laurent Pagnier, Robert Mieth +4
This paper addresses the challenge of efficiently solving the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Awar…
Machine Learning for Electricity Market Clearing
Laurent Pagnier, Robert Ferrando, Yury Dvorkin +1
This paper seeks to design a machine learning twin of the optimal power flow (OPF) optimization, which is used in market-clearing procedures by wholesale electricity markets. The m…