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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/22307
Title: A Comparative Evaluation of Data Mining Techniques for Fault Classification in TCSC Lines Using Multiclass Classification Approach
Authors: Kothari N.H.
Bhalja, Bhavesh R.
Pandya V.
Tripathi P.
Published in: Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021
2021 International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021
Abstract: This paper presents a comparative evaluation of data mining techniques such as Random Forest (RF), Support Vector Machine (SVM), and Naiïve Bayes Tree (NBTree) classifiers for classifying faults in Thyristor Controlled Series Compensated (TCSC) transmission lines. The performance of these classifiers has been evaluated as a multi-class classifier for classifying shunts faults in TCSC lines. The inputs given to the classifiers have been derived from instantaneous currents. The validity of the suggested technique has been tested by modeling a power system with 300 km long, 400 kV TCSC line in PSCAD/EMTDC. Wide variation in fault parameters and system conditions have been considered to generate faults cases for evaluating performance of the classifiers. The training of the classifiers has been carried out with 3,840 fault cases. The performance evaluation with 14,400 test fault cases indicates that the performance of RF classifiers has been consistent in comparison to SVM and NBTree classifiers for classifying faults in TCSC lines. © 2021 IEEE.
Citation: Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021 (2021): 994-998
URI: https://doi.org/10.1109/ICAIS50930.2021.9395809
http://repository.iitr.ac.in/handle/123456789/22307
Issue Date: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Fault classification
Naiïve Bayes Tree
Random Forest
Support Vector Machine
Thyristor Controlled Series Compensator
ISBN: 9.78E+12
Author Scopus IDs: 57215558973
12790894600
56020330300
57197259311
Author Affiliations: Kothari, N.H., Rk University, Department of Electrical Engineering, Rajkot, India
Bhalja, B.R., Indian Institute of Technology Roorkee, Department of Electrical Engineering, Roorkee, India
Pandya, V., Pandit Deendayal Petroleum University, Department of Electrical Engineering, Gandhinagar, India
Tripathi, P., Institute of Engineering and Technology, Dr. A.P.J. Abdul Kalam Technical University, Department of Electrical Engineering, Lucknow, India
Appears in Collections:Conference Publications [EE]

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