scholarly journals A Convolutional Neural Network for Detecting Faults in Power Distribution Networks along a Railway: A Case Study Using YOLO

Author(s):  
J. P. Augusto Costa ◽  
O. A. Carmona Cortes
2021 ◽  
Author(s):  
Huthaifa A. Al Issa ◽  
Iryna Trunova ◽  
Oleksandr Miroshnyk ◽  
Oleksandr Moroz ◽  
Oleksandr Savchenko ◽  
...  

2021 ◽  
Author(s):  
Dinara A. Japarova ◽  
Vyacheslav F. Kalinin ◽  
Sergey V. Kochergin ◽  
Alexander V. Kobelev ◽  
Lyudmila Yu. Korolyova

Author(s):  
Ronnielli Chagas de Oliveira ◽  
Fernando Venancio Amaral ◽  
Fagnielly Chagas Oliveira ◽  
Bruno Leonardo Fernandes Souza

2019 ◽  
Vol 9 (4) ◽  
pp. 296-306
Author(s):  
Seyed Morteza Moghim ◽  
Alireza Ashrafi Noosh Abadi ◽  
Mohammadreza Mehrara ◽  
Kobra Fathollah Zadeh ◽  
Fatemeh Eftekhari ◽  
...  

With respect to power distribution networks, which includes two types of air and ground networks; it is worth noting that the use of the air networks is more economical and therefore dominates the existing air networks. In this paper, the authors have worked on the reliability indexes changes for a month period. As well, the paper’s aim is to make a strategy in short-term (monthly) to network management in order to alleviate cutoff number and time, ENS, increasing customer satisfaction from electric distribution companies and comparing the performance of air and ground networks. The paper was done based on a case study sample substation of a network in Bakhtar regional electric company, Iran. Also, simulation results have obtained by CYME PSAF.


2019 ◽  
Vol 80 ◽  
pp. 02005
Author(s):  
Sambeet Mishra ◽  
Chiara Bordin ◽  
Jordi Mateo Fornes ◽  
Ivo Palu

Reliability of power system in terms of investments in network maintenance and restructuring for power distribution network has gained importance due to increase in distributed generation. To determine the reliability of the power distribution network, the state of power apparatus, losses in the network and consumer satisfaction indices are key factors. Considering the aforementioned, this paper proposes a holistic reliability framework for power distribution networks. The framework lists the following factors: life cycle of power apparatus, environmental and sociological, node reliability, arc reliability. A case study for reliability evaluation is performed on a modified IEEE 14 bus network. Furthermore, multiple scenarios of generation fault or outage are studied and results are presented. The key contribution of this paper is to present a novel and holistic reliability framework to model distribution network.


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