5 papers
A General Framework for Uncertainty Quantification via Neural SDE-RNN
Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan
Uncertainty quantification is a critical yet unsolved challenge for deep learning, especially for the time series imputation with irregularly sampled measurements. To tackle this p…
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids
Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan +1
Under a smart grid paradigm, there has been an increase in sensor installations to enhance situational awareness. The measurements from these sensors can be leveraged for real-time…
Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems
Shweta Dahale, Balasubramaniam Natarajan
The transition to a smarter grid is empowered by enhanced sensor deployments and smart metering infrastructure in the distribution system. Measurements from these sensors and meter…
Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System
Shweta Dahale, Balasubramaniam Natarajan
Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-bas…
Multi Time-scale Imputation aided State Estimation in Distribution System
Shweta Dahale, Balasubramaniam Natarajan
With the transition to a smart grid, we are witnessing a significant growth in sensor deployments and smart metering infrastructure in the distribution system. However, information…