Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids
Author:
Affiliation:
1. Kansas State University,Electrical and Computer Engineering,Manhattan,USA,KS-66506
2. Sensing and Predictive Analytics Group in the Power Systems Engineering Center of the National Renewable Energy Laboratory (NREL),Golden,CO,80401
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10066177/10066335/10066442.pdf?arnumber=10066442
Reference17 articles.
1. Neural ordinary differential equations;chen;Advances in neural information processing systems,2018
2. Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems
3. Fast and reliable distribution load and state estimator
4. Latent ordinary differential equations for irregularly-sampled time series;rubanova;Advances in neural information processing systems,2019
5. Electric Power Network State Tracking From Multirate Measurements
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