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High-impedance fault detection in power distribution grid systems based on support vector machine approach

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Abstract

Today, microgrids are used increasingly in different types because of its several financial and environmental benefits for customers, societies and nations. Its implementation, however, makes significant theoretical and practical challenges, such as fault detection that could make crucial damage to the utility grid and microgrids. This paper, accordingly, developed a novel, fast and accurate method based on Support Vector Machines (SVM) approach for High Impedance Fault (HIF) detection. The proposed method applied to a typical distributed generation system for detecting single line, double line and triple line HIFs. Also, the behavior of current signals of the other phases are investigated during faults occurrence. The simulation results show how this algorithm can separate faults condition among the other fault-like phenomena and gets a better response in comparison to present methods like Wavelet Transformation (WT) and Artificial Neural Networks (ANN). This method will boost the development of renewable energy usage by reducing fault detection delays and operational risks.

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All the data and materials related to this study are available.

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All simulations and results which are implemented in MATLAB software are available.

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Authors and Affiliations

  1. Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

    Ali Ahmadi, Ebrahim Aghajari & Mehdi Zangeneh

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  1. Ali Ahmadi
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  2. Ebrahim Aghajari
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  3. Mehdi Zangeneh
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Correspondence to Ebrahim Aghajari.

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Ahmadi, A., Aghajari, E. & Zangeneh, M. High-impedance fault detection in power distribution grid systems based on support vector machine approach. Electr Eng 104, 3659–3672 (2022). https://doi.org/10.1007/s00202-022-01544-1

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