High-impedance fault detection and classification in power system distribution networks using morphological fault detector algorithm

2018 ◽  
Vol 12 (15) ◽  
pp. 3699-3710 ◽  
Author(s):  
Moses Kavi ◽  
Yateendra Mishra ◽  
Mahinda D. Vilathgamuwa
Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2331 ◽  
Author(s):  
Saeid Khavari ◽  
Rahman Dashti ◽  
Hamid Reza Shaker ◽  
Athila Santos

Power distribution networks are vulnerable to different faults, which compromise the grid performance and need to be managed effectively. Automatic and accurate fault detection and location are key components of effective fault management. This paper proposes a new framework for fault detection and location for smart distribution networks that are equipped with data loggers. The framework supports networks with mixed overhead lines and underground cables. The proposed framework consists of area detection, faulty section identification, and high impedance fault location. Firstly, the faulty zone and section are detected based on the operation of over-current relays and digital fault recorders. Then, by comparing the recorded traveling times at both ends of lines, which are related to the protection zone, the faulty line is identified. In the last step, the location of the fault is estimated based on discrete wavelet transform. The proposed method is tested on a 20 kV 13 node network, which is composed of overhead lines and underground cables. The method is tested in both balanced and unbalanced configurations. The obtained results confirm the advantages of the proposed method compared with the current state-of-the art.


Author(s):  
Érica Mangueira Lima ◽  
Rodrigo de Almeida Coelho ◽  
Núbia Silva Dantas Brito ◽  
Benemar Alencar de Souza

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