Design and Implementation of a Machine Learning State Estimation Model for Unobservable Microgrids-Reference-Cited by-同舟云学术

Design and Implementation of a Machine Learning State Estimation Model for Unobservable Microgrids

Published:2022 Issue: Volume:10 Page:123387-123398
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Acuna Acurio Byron Alejandro¹^ORCID,Barragan Diana Estefania Cherrez¹^ORCID,Amezquita Juan Camilo Lopez¹,Rider Marcos J.¹^ORCID,Silva Luiz Carlos Pereira Da¹

Affiliation:

1. Department of Systems and Energy, School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas, Brazil

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09963949.pdf?arnumber=9963949

Reference65 articles.

1. Dynamic Detection of Transmission Line Outages Using Hidden Markov Models

2. Local and Wide-Area PMU-Based Decentralized Dynamic State Estimation in Multi-Machine Power Systems

3. State Estimation in Smart Distribution Systems with Deep Generative Adversary Networks

4. Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning

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