Smart Fault detection and classifcation scheme for Active electrical distribution networks based on Low Pass Filtering approch
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DOI:
https://doi.org/10.59287/ijanser.55Keywords:
Active distribution networks, Faults detection and Classifcation, Low Pass Filtering, Renewable energy resourcesAbstract
The latest developments and trends in electrical distribution networks is the large scale penetration of renewable energy resources near consumer territory. These renewable energy-penetrated distribution networks are called active distribution networks (ADN’s), which have large amount of envoi mental and economical benefits. However, the faults detection and classifcation is an issue in such ADN’s due to the low current level during faults, and bidirectional power flows. This paper establishes a new fault detection as well as classification method for the ADN’s, using Low Pass Filtering (LPF) approach. Initial, LPF is applied to the current signal of each phase separately, to extract the desired filtered features (DFF). Furthermore, these DFF are utilized to calculate single-phase fault detection index and classification (SPFD&CI) independently. If the SPFD&CI of any singular phase is more than a constant threshold value (Tc), the associated phase is deliberately faulty. However, the fault classification is autonomous due to phase segregation. The proposed approach is tested on the ADN’s test system in MATLAB/Simulink software. Results demonstrate that the proposed approch detects and classifies all kind of faults in less than half cycle under different topologies, and worst cases.
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