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Time-Synchronized State Estimation Using Graph Neural Networks in Presence of Topology Changes
Recently, there has been a major emphasis on developing data-driven approaches involving machine learning (ML) for high-speed static state estimation (SE) in power systems.
Data-Driven Flow and Injection Estimation in PMU-Unobservable Transmission Systems
Fast and accurate knowledge of power flows and power injections is needed for a variety of applications in the electric grid.
Monitoring and Detection of Low-current High-Impedance Faults in Distribution Networks
To date, we have built a physical test facility for power system fault analysis and developing and evaluating our sensing and fault detection system.
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