Application of Artificial Neural Network-Based Tool for Short Circuit Currents Estimation in Power Systems With High Penetration of Power Electronics-Based Renewables-Reference-Cited by-同舟云学术

Application of Artificial Neural Network-Based Tool for Short Circuit Currents Estimation in Power Systems With High Penetration of Power Electronics-Based Renewables

Published:2023 Issue: Volume:11 Page:20051-20062
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Aljarrah Rafat¹^ORCID,Al-Omary Murad²^ORCID,Alshabi Dua'a²^ORCID,Salem Qusay¹^ORCID,Alnaser Sahban³^ORCID,Ćetenović Dragan⁴^ORCID,Karimi Mazaher⁵^ORCID

Affiliation:

1. Electrical Engineering Department, Princess Sumaya University for Technology, Amman, Jordan

2. Energy Engineering Department, German Jordanian University, Amman, Jordan

3. Electrical Engineering Department, The University of Jordan, Amman, Jordan

4. Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, U.K

5. School of Technology and Innovations, University of Vaasa, Vaasa, Finland

Funder

University of Vaasa through the Centralized Intelligent and Resilient Protection Schemes for Future Grids Applying 5G (CIRP-5G) Research Project by Business Finland

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/ielx7/6287639/10005208/10054036.pdf?arnumber=10054036

Reference31 articles.

1. Experimental study on short-circuit current characteristics of a photovoltaic system with low voltage ride through capability under a symmetrical fault

2. A review of fault ride through of PV and wind renewable energies in grid codes

3. Modelling fault behaviour of power electronic converters

4. Fault response of inverter interfaced distributed generators in grid-connected applications

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