An improved high-impedance fault identification scheme for distribution networks based on kernel extreme learning machine
Author:
Publisher
Elsevier BV
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology
Reference28 articles.
1. Modelling and detection of live tree-related high impedance fault in distribution systems;Bahador;IET Gener Transm Distrib,2018
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4. Real-time detection of transients induced by high-impedance faults based on the boundary wavelet transform;Costa;IEEE Trans Industry Appl.,2015
5. Detection and location of high impedance faults in multi-conductor overhead distribution lines using power line communication devices;Milioudis;IEEE Trans Smart Grid,2015
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1. Fault classification and localization of multi-machine-based ieee benchmark test case power transmission lines using optimizable weighted extreme learning machine;Electric Power Systems Research;2024-10
2. Reliable high impedance fault detection method based on the roughness of the neutral current in active distribution systems;International Journal of Electrical Power & Energy Systems;2024-08
3. Applications of tunable-Q factor wavelet transform and AdaBoost classier for identification of high impedance faults: Towards the reliability of electrical distribution systems;Energy Exploration & Exploitation;2024-06-11
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