3 citations · 3 across the 8 of their papers we have counts for
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Adaptive State Estimation Under Topological Uncertainty in Unobservable Primary Distribution Systems Using Strategically Placed Sensors
Farah Elsherif, Behrouz Azimian, Anamitra Pal
The rapid integration of distributed energy resources is fundamentally altering power flow patterns in primary distribution networks and intensifying operational uncertainty. These…
Machine Learning-Based State Estimation for an Actual Transmission System Using Field PMU Data
Shiva Moshtagh, Nihar Thakkar, Anamitra Pal +1
Time-synchronized state estimation (SE) plays a critical role in ensuring real-time situational awareness in modern power systems. However, achieving full system observability usin…
A Constrained Formulation for Simultaneous Line Parameter Estimation and Instrument Transformer Calibration
Antos Cheeramban Varghese, Rajasekhar Anguluri, Anamitra Pal
The process of calibrating instrument transformers (ITs) has been greatly simplified by using phasor measurement unit (PMU) data since this process eliminates the need for (a) addi…
Topology-Aware Graph Neural Network-based State Estimation for PMU-Unobservable Power Systems
Shiva Moshtagh, Behrouz Azimian, Mohammad Golgol +1
Traditional optimization-based techniques for time-synchronized state estimation (SE) often suffer from high online computational burden, limited phasor measurement unit (PMU) cove…
System-wide Instrument Transformer Calibration and Line Parameter Estimation Using PMU Data
Antos Cheeramban Varghese, Anamitra Pal
Uncalibrated instrument transformers (ITs) can degrade the performance of downstream applications that rely on the voltage and current measurements that ITs provide. It is also wel…
Cut-set and Stability Constrained Optimal Power Flow for Resilient Operation During Wildfires
Satyaprajna Sahoo, Anamitra Pal
Resilient operation of the power system during ongoing wildfires is challenging because of the uncertain ways in which the fires impact the electric power infrastructure (multiple…