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Dual-tree complex wavelet packet transform and regularized extreme learning machine-based feature extraction and classification of power quality disturbances

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Abstract

There is an urgency to monitor, detect and classify the power quality disturbances (PQDs) due to global concern of the exponential increase of power quality (PQ) and the penetration of renewable energy sources (RESs) through power electronics-based interfacing devices to the power system. In this study, an intelligent method based on dual-tree complex wavelet packet transform (DTCWPT) is used to extract the frequency-domain features from the frequency-band signals to reveal PQ characteristics. To classify the PQDs, a regularized extreme learning machine (RELM) is used in which regularized regression method pruning the ELM by a computed suitable number of the hidden nodes in the network architecture. To test the efficiency of the proposed approach, the system is verified with eight PQDs with noise addition and multiple occurrence events cases and, at last, with practical signals generated from a PC interfaced hardware prototype. The proposed approach results in satisfactory performance for the PQ analysis and can be considered as the traditional PQ analyzer in real-time conditions.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Siksha’ O’ Anusandhan University, Odisha, India

    Indu Sekhar Samanta & Satyasis Mishra

  2. Department of Electrical and Electronics Engineering, Siksha’ O’ Anusandhan University, Odisha, India

    Pravat Kumar Rout

  3. Department of Electrical and Electronics Engineering, National Institute of Science and Technology, Odisha, India

    Kunjabihari Swain & Murthy Cherukuri

Authors
  1. Indu Sekhar Samanta
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  2. Pravat Kumar Rout
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  3. Kunjabihari Swain
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  4. Murthy Cherukuri
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  5. Satyasis Mishra
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Correspondence to Indu Sekhar Samanta.

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Samanta, I.S., Rout, P.K., Swain, K. et al. Dual-tree complex wavelet packet transform and regularized extreme learning machine-based feature extraction and classification of power quality disturbances. Energy Syst (2023). https://doi.org/10.1007/s12667-023-00584-1

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