TY - JOUR
T1 - A comprehensive backup protection for transmission lines based on an intelligent wide‐area monitoring system
AU - Petite, Fernanda Soares Vitor
AU - Santos, Ricardo Caneloi
AU - Junior, Giovanni Manassero
AU - Yang, Qingqing
AU - Li, Jianwei
PY - 2021/5
Y1 - 2021/5
N2 - This work presents the development, implementation and evaluation of an accurate intelligent wide-area monitoring system for supporting protection functions in transmission lines. The proposed scheme is based on artificial neural networks and uses only postfault voltage signals for fault detection, classification, and location in transmission lines with different characteristics. The development and evaluation of the proposed intelligent system were based on three different electric power grids, under several different fault conditions (fault type, location, and resistance). The electrical systems were modeled in Matlab and PSCAD, while the proposed algorithm was developed in Matlab. The results are promising, showing that the proposed scheme presents a high level of accuracy and robustness. Moreover, the comprehensiveness of the presented solution is proven against three different power grids.
AB - This work presents the development, implementation and evaluation of an accurate intelligent wide-area monitoring system for supporting protection functions in transmission lines. The proposed scheme is based on artificial neural networks and uses only postfault voltage signals for fault detection, classification, and location in transmission lines with different characteristics. The development and evaluation of the proposed intelligent system were based on three different electric power grids, under several different fault conditions (fault type, location, and resistance). The electrical systems were modeled in Matlab and PSCAD, while the proposed algorithm was developed in Matlab. The results are promising, showing that the proposed scheme presents a high level of accuracy and robustness. Moreover, the comprehensiveness of the presented solution is proven against three different power grids.
KW - artificial neural networks
KW - fault location
KW - pattern recognition
KW - monitoring system
UR - http://www.scopus.com/inward/record.url?scp=85102935673&partnerID=8YFLogxK
U2 - 10.1002/2050-7038.12870
DO - 10.1002/2050-7038.12870
M3 - Article
SN - 2050-7038
VL - 31
JO - International Transactions on Electrical Energy Systems
JF - International Transactions on Electrical Energy Systems
IS - 5
M1 - e12870
ER -