Hybrid travelling wave and ANN for fault location in branched distribution network

Jahanger, Hayder K., Kherif, Omar, Robson, Stephen ORCID: https://orcid.org/0000-0003-3156-1487 and Haddad, Manu ORCID: https://orcid.org/0000-0003-4153-6146 2024. Hybrid travelling wave and ANN for fault location in branched distribution network. Presented at: 17th International Conference on Developments in Power System Protection, Manchester, UK, 04-07 March 2024. Proceedings of the 17th International Conference on Developments in Power System Protection (DPSP 2024). IEEE, pp. 155-161. 10.1049/icp.2024.0891

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Abstract

The fault location in distribution network with multiple branches and mixed overhead lines and underground cable is of vital importance. A hybrid approach that combines Artificial Neural Network (ANN) and travelling wave based double-ended method in distribution network with multiple branches and mixed lines is investigated. An ANN is trained using limited amount of measurement to identify the faulty section in four terminals distribution network. Then, a double-ended traveling wave fault location is applied using terminals choice based on the ANN decision. The training data is generated using ATP-EMTP simulation software and the data processed using CWT to extract Time of Arrival (ToA) and analysed using MATLAB script. The analysis showed that the ANN is capable to identify fault section with accuracy of 90% or more while the fault location accuracy is within 99%. The algorithm is resilience to fault resistance, inception angle and fault types while it is influenced by the system added noise. However, analysing the recorded signal with multiple CWT levels enable the correct extraction of the fault wave arrival time.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	IEEE
ISBN:	9781837240852
Last Modified:	02 Oct 2024 12:45
URI:	https://orca.cardiff.ac.uk/id/eprint/172431

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