A fast fault detection and identification approach in power distribution systems
Document Type
Conference Proceeding
Publication Date
8-1-2019
Publication Title
5th International Conference on Power Generation Systems and Renewable Energy Technologies, PGSRET 2019
Keywords
Fault Detection, Fault Identification, Modified Multi-Class Support Vector Machines (MMC-SVM)., Power Distribution Systems
Abstract
© 2019 IEEE. In this paper, a Modified Multi-Class Support Vector Machines (MMC-SVM) technique is developed to simultaneously detect and classify different types of open-circuit faults in power distribution systems. This technique is capable of detecting and identifying open-circuit faults considering the impact of variations in the voltage of different nodes in power distribution systems. The RMS (Root Mean Square) voltage of the power grid is used as the input signal to diagnose the faults. Simulations are carried out on the IEEE 13-node test system considering temporary open-circuit faults in MATLAB software. The simulation results show the accuracy, effectiveness, and robustness of the proposed method.
DOI
10.1109/PGSRET.2019.8882676
Recommended Citation
Mohammadi, Fazel; Nazri, Gholam Abbas; and Saif, Mehrdad. (2019). A fast fault detection and identification approach in power distribution systems. 5th International Conference on Power Generation Systems and Renewable Energy Technologies, PGSRET 2019.
https://scholar.uwindsor.ca/electricalengpub/32