Skip to main content

Research Repository

Advanced Search

Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering

Silva, HCE; Saraee, MH

Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering Thumbnail


Authors

HCE Silva



Abstract

In-depth understanding of a fault cause in electricity distribution network has always been of paramount importance to Distributed Network Operators (DNO) for a reliable power supply. Faults in the network have direct effect on its stability, availability and maintenance; and so, their quick elimination, prevention and avoidance of fault causes that generated them, is of special interest. Possible opportunity to understanding the causes and correlation of the factors where future faults may arise can significantly help electricity distribution operators who happen to be accountable to detect and repair such problems. Every asset in the distribution network has a different level of reliability and which may vary. Faults identifying in distribution network have rich literature but a very few studies had been done on understanding the factors that contribute to LV Faults using data mining and machine learning techniques. As there are lack of studies on Faults identifying in distribution network with data mining, this study will formulate a starting point. This paper aims to use the association rule mining and clustering techniques to understand the various hidden patterns from the faults database. The uncovered relationships can be represented in the form of Association rules and clusters. The outcomes of this research will hugely beneficial to the engineering departments in DNOs. New knowledge gain from this study will help to priorities investments in new or replacement infrastructure which will ensure that financial and manpower resources are used more efficiently.

Citation

Silva, H., & Saraee, M. (2019, June). Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering. Presented at 3RD IEEE Industrial and Commercial Power System Europe (I&CPS), Genoa, Italy

Presentation Conference Type Other
Conference Name 3RD IEEE Industrial and Commercial Power System Europe (I&CPS)
Conference Location Genoa, Italy
Start Date Jun 11, 2019
End Date Jun 14, 2019
Acceptance Date Apr 1, 2019
Publication Date Aug 1, 2019
Deposit Date Apr 4, 2019
Publicly Available Date Jun 15, 2019
Book Title 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
ISBN 9781728106533;-9781728106540;-9781728106526
DOI https://doi.org/10.1109/EEEIC.2019.8783949
Publisher URL http://dx.doi.org/ 10.1109/EEEIC.2019.8783949
Related Public URLs https://www.eeeic.net/eeeic/
Additional Information Event Type : Conference

Files






You might also like



Downloadable Citations