TY - GEN
T1 - Neuro wavelet algortihm for detecting high impedance faults in extra high voltage transmission systems
AU - Hafidz, Isa
AU - Nofi, P. Elyza
AU - Anggriawan, DImas Okky
AU - Priyadi, Ardyono
AU - Pumomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/16
Y1 - 2017/6/16
N2 - High impedance faults are not easy to be measured and detected by convetional relay protection. This paper proposed simualtions studies for detection high impedance fault in extra high voltage transmission line (EVT). The fault simulations based on simplified 2 diodes model. Current signal from the measurement is processed using discrete wavelet transform type haar wavelet to obtain coefficient detail. The output of discrete wavelet transform will be used for pattern recognition based on an backpropagation neural networks algorithm. The fault is modified to distribution system for EVT. The Characteristics of the proposed scheme are analyzed by comprehensive studies and the result clearly explain that it can accurately detect high impedance fault in the EVT with varies condition.
AB - High impedance faults are not easy to be measured and detected by convetional relay protection. This paper proposed simualtions studies for detection high impedance fault in extra high voltage transmission line (EVT). The fault simulations based on simplified 2 diodes model. Current signal from the measurement is processed using discrete wavelet transform type haar wavelet to obtain coefficient detail. The output of discrete wavelet transform will be used for pattern recognition based on an backpropagation neural networks algorithm. The fault is modified to distribution system for EVT. The Characteristics of the proposed scheme are analyzed by comprehensive studies and the result clearly explain that it can accurately detect high impedance fault in the EVT with varies condition.
KW - haar wavelet transform
KW - high impedance faults
KW - pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=85025161705&partnerID=8YFLogxK
U2 - 10.1109/ICSREE.2017.7951519
DO - 10.1109/ICSREE.2017.7951519
M3 - Conference contribution
AN - SCOPUS:85025161705
T3 - 2017 International Conference on Sustainable and Renewable Energy Engineering, ICSREE 2017
SP - 97
EP - 100
BT - 2017 International Conference on Sustainable and Renewable Energy Engineering, ICSREE 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Sustainable and Renewable Energy Engineering, ICSREE 2017
Y2 - 10 May 2017 through 12 May 2017
ER -