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A Fault Diagnostic Protection Scheme Technique for a Grid-Integrated Power Distribution System


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DOI: https://doi.org/10.15866/iree.v18i3.23095

Abstract


The increase in energy demand due to rapid population growth, industrialization, depleting fossil energy resources, distribution network congestion, and environmental concerns of fossil fuels used to generate electricity are some of the reasons behind the integration of renewable Distributed Generation (DG) units into the existing power grid. Integrating DGs into the existing distribution network makes the system more flexible and increases power availability for the load demand increment. Although there are significant technical benefits of integrating DGs into the power grid, protection philosophy has been affected by these network topologies. This paper proposes a hybrid fault protection scheme in a power-integrated system. The proposed technique aims at minimizing the impact of the fault in the design and appropriately locating the position of the fault. The proposed approach comprises a signal processing and feature extraction segment using the Wavelet Packet Transform (WPT), a fault classification and detection segment using the Support Vector Machine (SVM), and a fault location segment using the Gaussian Process Regression (GPR). Subsequently, these techniques are combined to design a hybrid protection scheme. The scheme is tested by using a modified Eskom power system network and modeled in Power Factory Software. The classification and the regression functions are implemented by using the MATLAB platform. The proposed technique's main contribution is the scheme's ability to classify, detect, and locate fault using a ½ cycle of the fault signal window. The results show that the proposed system has achieved a 99.8% classification accuracy and a minimum fault estimation error.
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Keywords


Fault Classification; Fault Location; Gaussian Process Regression; Stationary Wavelet Transform; Support Vector Machine

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References


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