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Hybrid Approach for Detection and Diagnosis of Short-Circuit Faults in Power Transmission Lines
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In this article, the main problem under investigation is the detection and diagnosis of short-circuit faults in power transmission lines. The proposed fault detection (FDD) approach is mainly based on principal component analysis (PCA). The proposed fault diagnosis/identification (FAI) approach is mainly based on sliding-window versions of the discrete Fourier transform (DFT) and discrete Hilbert transform (DHT). The main contributions of this article are (a) a fault detection approach based on principal component analysis in the two-dimensional scores space; and (b) a rule-based fault identification approach based on human expert knowledge, combined with a probabilistic decision system, which detects variations in the amplitudes and frequencies of current and voltage signals, using DFT and DHT, respectively. Simulation results of power transmission lines in Portugal are presented in order to show the robust and high performance of the proposed FDD approach for different signal-to-noise ratios. The proposed FDD approach, implemented in Python, that can be executed online or offline, can be used to evaluate the stress to which circuit breakers (CBs) are subjected, providing information to supervision- and condition-based monitoring systems in order to improve predictive and preventive maintenance strategies, and it can be applied to high-/medium-voltage power transmission lines as well as to low-voltage electronic transmission systems.
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Funding Information:
The APC was funded by the H2020 BD4NRG European Project and by the UNINOVA research institute (https://www.uninova.pt(accessed on 28 March 2024)).
This work has been supported by H2020 BD4NRG European Project—GA872613, https://www.bd4nrg.eu/ (accessed on 18 March 2024), by Department of Electrical and Computer Engineering of NOVA School of Science and Technology (FCT NOVA), by CTS-UNINOVA and LASI research units, and by national funds through FCT-Fundação para a Ciência e a Tecnologia within the Research unit CTS—Centro de Tecnologia e Sistemas. The authors would like to thank all the institutions, and also thank the REN company and the R&D Nester ID center, for the simulation data made available and for the exchange of knowledge. Colleagues Pedro Maló, Rui Azevedo Antunes and Paulo Gil deserve thanks for their support in some phases of the H2020 BD4NRG European Project.
Publisher Copyright:
© 2024 by the author.
Palavras-chave
discrete Fourier transform discrete Hilbert transform power transmission lines principal component analysis rule-based fault detection and diagnosis approach short-circuit faults and circuit breakers Renewable Energy, Sustainability and the Environment Fuel Technology Engineering (miscellaneous) Energy Engineering and Power Technology Energy (miscellaneous) Control and Optimization Electrical and Electronic Engineering SDG 7 - Affordable and Clean Energy