Abstract
This paper deals with the fault identification in generator and load buses of an isolated renewable energy conversion system, monitoring the Skewness and Kurtosis values of the wavelet decomposition level coefficients. In this study, a standalone wind energy conversion scheme has been considered and the source and load currents at normal and at LL (line to line), LLG (double line to ground), and LG (line to ground) faults have been recorded and analyzed using Multi-Resolution Analysis of Discrete Wavelet Transform (MRA of DWT). Statistical value monitoring of the wavelet decomposition level coefficients have been pursued to extract some feature patterns for identifying the various faults and zone of occurrence of these faults in the system. The features obtained can also be used for other type of simulated and real time systems, for identification of other type of faults in the network.
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Ray, D.K., Chattopadhyay, S., Sengupta, S. (2019). Fault Diagnosis in Isolated Renewable Energy Conversion System Using Skewness and Kurtosis Assessment. In: Chattopadhyay, S., Roy, T., Sengupta, S., Berger-Vachon, C. (eds) Modelling and Simulation in Science, Technology and Engineering Mathematics. MS-17 2017. Advances in Intelligent Systems and Computing, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-74808-5_7
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DOI: https://doi.org/10.1007/978-3-319-74808-5_7
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