Incipient fault monitoring of medium voltage UD-EPR power cable using Rogowski coil

Author(s):  
Farshid Naseri ◽  
Teymoor Ghanbari ◽  
Ebrahim Farjah
2020 ◽  
Vol 9 (2) ◽  
pp. 427-435
Author(s):  
A. Z. Abdullah ◽  
M. Isa ◽  
M. N. K. H. Rohani ◽  
H. A. Hamid ◽  
M. H. Amlus ◽  
...  

This paper presents the modelling of the online partial discharge (PD) measurement of the medium voltage (MV) power cable. Recently, PD monitoring trends are rapidly increasing due to high demand on reliable systems. Degradation are mainly due to the presence of PD in the high voltage power equipment used. PD measurement is therefore a highly recommended task to early detection of the degradation insulation for high voltage (HV) equipment in order to avoid breakdowns. Real network modelling is necessary to improvise system design in order to find the efficiency in a real power system network. In this paper, modelling focuses on a real distribution network by applying Rogowski coil (RC) as a detection sensor to trigger PD activity. The simulation is performed to determine the functionality and reliability of the system with the RC application in the network. The analysis is performed in the ATP-EMTP and MATLAB Simulink software environments. In addition, this paper contributed to justify the approach of a simplified PD sensor and measurement system. This PD measurement system provides a complete solution in the context of condition-oriented monitoring for the ability to apply the RC to trigger PD activity in the power distribution network. 


Author(s):  
A. Z. Abdullah ◽  
M. Isa ◽  
M. N. K. H. Rohani ◽  
S. A. S. Jamalil ◽  
A. N. N. Abdullah ◽  
...  

This paper presents, the development of smart online partial discharge (PD) monitoring system for medium voltage (MV) underground power cable. PD monitoring is the highly efficient tool to monitor insulation degradation for high voltage (HV) equipment in order to avoid failures or breakdown. Selection of improved technology and performance of PD detection sensor, effective measurement technique and smart user friendly of graphical user interface (GUI) system are contributed towards the development of efficient monitoring system. This paper addresses three main aspects which are needed in completing the monitoring system. They are, the use of Rogowski coil (RC) as detection sensor, processing unit using Alterra board and integrated with GUI PD monitoring system for underground cable using LabVIEW. The monitoring system is compared to the conventional method with the PD signal used is measured from the real on-site measurement in order to analyse its performance. The analysis is performed in MATLAB and LabVIEW software’s environment and the maximum peak of PD signal is enabled to view using GUI which complete with the location information of PD source. Furthermore, this paper has contributed to solve the problem in selection the simplified and practical approach for PD sensor and monitoring system. In the perspective of automated condition monitoring, this smart online PD monitoring system provides a complete solution towards latest industrial revolutions


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4116
Author(s):  
Krzysztof Siodla ◽  
Aleksandra Rakowska ◽  
Slawomir Noske

A medium voltage (MV) cable network is a substantial component of the distribution network. Present management of this grid segment is mainly based on the failure rate analysis, i.e., a rise in the number and kind of faults on the actual line means that its technical condition is getting worse. The efficiency of the power system is low and additional costs of repair works, supply interruption, difficulties in the investment planning and operation and maintenance works are necessary. The aim of the R&D works done in the realised project is to implement the management of the MV cable network based on the estimated condition of the individual cable line, obtained from diagnostic measurements. The diagnostic investigations of the cable lines are the reference. Many years of research work have led to the development of the Health Index based on diagnostic, technical and service data.


2017 ◽  
Vol 32 (3) ◽  
pp. 1450-1459 ◽  
Author(s):  
Wenhai Zhang ◽  
Xianyong Xiao ◽  
Kai Zhou ◽  
Wilsun Xu ◽  
Yindi Jing

2013 ◽  
Vol 7 (5) ◽  
pp. 526-536 ◽  
Author(s):  
Christos G. Kaloudas ◽  
Kostas V. Gouramanis ◽  
Konstantinos Stasinos ◽  
Grigoris K. Papagiannis ◽  
Theofilos A. Papadopoulos

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