24 citations · 76 across the 58 of their papers we have counts for
9 papers · 2 filters
Data-driven identification of a thermal network in multi-zone building
Harish Doddi, Saurav Talukdar, Deepjyoti Deka +1
System identification of smart buildings is necessary for their optimal control and application in demand response. The thermal response of a building around an operating point can…
Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks
Wenting Li, Deepjyoti Deka, Michael Chertkov +1
Diverse fault types, fast re-closures, and complicated transient states after a fault event make real-time fault location in power grids challenging. Existing localization techniqu…
Physics Informed Topology Learning in Networks of Linear Dynamical Systems
Saurav Talukdar, Deepjyoti Deka, Harish Doddi +3
Learning influence pathways of a network of dynamically related processes from observations is of considerable importance in many disciplines. In this article, influence networks o…
Is Machine Learning in Power Systems Vulnerable?
Yize Chen, Yushi Tan, Deepjyoti Deka
Recent advances in Machine Learning(ML) have led to its broad adoption in a series of power system applications, ranging from meter data analytics, renewable/load/price forecasting…
Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow
Ali Hassan, Robert Mieth, Michael Chertkov +2
Distribution system operators (DSO) world-wide foresee a rapid roll-out of distributed energy resources. From the system perspective, their reliable and cost effective integration…
Joint Estimation of Topology and Injection Statistics in Distribution Grids with Missing Nodes
Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Optimal operation of distribution grid resources relies on accurate estimation of its state and topology. Practical estimation of such quantities is complicated by the limited pres…
Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids
Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Distribution grid is the medium and low voltage part of a large power system. Structurally, the majority of distribution networks operate radially, such that energized lines form a…
Learning with End-Users in Distribution Grids: Topology and Parameter Estimation
Sejun Park, Deepjyoti Deka, Scott Backhaus +1
Efficient operation of distribution grids in the smart-grid era is hindered by the limited presence of real-time nodal and line meters. In particular, this prevents the easy estima…
Topology Learning of Radial Dynamical Systems with Latent Nodes
Saurav Talukdar, Deepjyoti Deka, Michael Chertkov +1
In this article, we present a method to reconstruct the topology of a partially observed radial network of linear dynamical systems with bi-directional interactions. Our approach e…