Employing Machine Learning for Enhancing Transient Stability of Power Synchronization Control During Fault Conditions in Weak Grids-Reference-Cited by-同舟云学术

Employing Machine Learning for Enhancing Transient Stability of Power Synchronization Control During Fault Conditions in Weak Grids

Published:2022-05 Issue:3 Volume:13 Page:2121-2131
ISSN:1949-3053
Container-title:IEEE Transactions on Smart Grid
language:
Short-container-title:IEEE Trans. Smart Grid

Author:

Sepehr Amir¹^ORCID,Gomis-Bellmunt Oriol²^ORCID,Pouresmaeil Edris¹^ORCID

Affiliation:

1. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland

2. Departament d’Enginyeria Electrica, Centre d’Innovació Tecnologica en Convertidors Estatics i Accionaments, Universitat Politecnica de Catalunya, Barcelona, Spain

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/5165411/9761268/09701593.pdf?arnumber=9701593

Reference29 articles.

1. Nonlinear and Transient Stability Analysis of Phase-Locked Loops in Grid-Connected Converters

2. Transient Stability Analysis and Enhancement of Renewable Energy Conversion System During LVRT

3. Transient Angle Stability of Paralleled Synchronous and Virtual Synchronous Generators in Islanded Microgrids

4. Transient Stability Analysis of Grid-Tied Converters Considering PLL’s Nonlinearity

5. An Overview of Assessment Methods for Synchronization Stability of Grid-Connected Converters Under Severe Symmetrical Grid Faults

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