DocumentCode
1861658
Title
Bus protection ANN model with function approximation ability
Author
Jian, Luo ; Guanglei, Yu ; Hua, Yang ; Hongwei, Zhao ; Bing, Ai
Author_Institution
Key Laboratory of High Voltage Eng. & Electr. New Technol., Chongqing Univ.
fYear
2005
fDate
Nov. 29 2005-Dec. 2 2005
Firstpage
1
Lastpage
478
Abstract
For a long time, the application of ANN to relay protection is based on classification ability. Enough fault samples are crucial for the performance of the protection, but limited sample data can be actually available for the training of ANN model. In order to overcome the drawback, bus protection based on ANN model with function approximation ability is presented in this paper. Function approximation is one of the most important ability of ANN, a function object can be replaced by an ANN model with function approximation ability. Physical object of bus protection is a function with certain relation between inputs and outputs, which can be replaced by an ANN model, i.e. can be approximated by an ANN mathematical model. Based on the ANN model trained under normal bus operation conditions, the inner or outer fault can be distinguished successfully
Keywords
busbars; neural nets; power engineering computing; power system protection; relay protection; ANN mathematical model; ANN model training; bus protection; relay protection; Artificial intelligence; Artificial neural networks; Function approximation; Mathematical model; Power system faults; Power system modeling; Power system protection; Power system relaying; Power system reliability; Protective relaying; Bus protection; artificial neural network; function approximation;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering Conference, 2005. IPEC 2005. The 7th International
Conference_Location
Singapore
Print_ISBN
981-05-5702-7
Type
conf
DOI
10.1109/IPEC.2005.206955
Filename
1627244
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