TY - GEN
T1 - Analysis of Power Transformer's Lifetime Using Health Index Transformer Method Based on Artificial Neural Network Modeling
AU - Nurcahyanto, Himawan
AU - Nainggolan, Jannus Maurits
AU - Ardita, I. Made
AU - Hudaya, Chairul
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Transformers play a big role in the distribution of electrical energy. One of the factors that determines the reliability level of the transformer is the life of the transformer. If the transformer is used longer, the level reliability of its transformer will be decrease. The purpose of this research was to predict the life of a transformer based on the health index transformer calculation, then the value of health index transformer will be modeled by using artificial neural network. The results of this research were the values used as the parameters in transformer testing, which were insulating oil, furan, and dissolved gas. One of the advantages of artificial neural network methods in predicting the life of the transformer is a calculation error that can be minimized. From the result of this research, the transformer's life prediction system can be used directly to determine the lives of other transformers, both new and operating ones, with a low percentage of errors. Furthermore, this method can be used as an option in maintaining power transformers.
AB - Transformers play a big role in the distribution of electrical energy. One of the factors that determines the reliability level of the transformer is the life of the transformer. If the transformer is used longer, the level reliability of its transformer will be decrease. The purpose of this research was to predict the life of a transformer based on the health index transformer calculation, then the value of health index transformer will be modeled by using artificial neural network. The results of this research were the values used as the parameters in transformer testing, which were insulating oil, furan, and dissolved gas. One of the advantages of artificial neural network methods in predicting the life of the transformer is a calculation error that can be minimized. From the result of this research, the transformer's life prediction system can be used directly to determine the lives of other transformers, both new and operating ones, with a low percentage of errors. Furthermore, this method can be used as an option in maintaining power transformers.
KW - artificial neural network
KW - health index transformer
KW - lifetime prediction
KW - power transformer
UR - http://www.scopus.com/inward/record.url?scp=85085857692&partnerID=8YFLogxK
U2 - 10.1109/ICEEI47359.2019.8988870
DO - 10.1109/ICEEI47359.2019.8988870
M3 - Conference contribution
AN - SCOPUS:85085857692
T3 - Proceedings of the International Conference on Electrical Engineering and Informatics
SP - 574
EP - 579
BT - Proceeding of 2019 International Conference on Electrical Engineering and Informatics, ICEEI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Electrical Engineering and Informatics, ICEEI 2019
Y2 - 9 July 2019 through 10 July 2019
ER -