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Discrimination of Transformer Inrush Currents and Internal Fault Currents Using Extended Kalman Filter Algorithm (EKF)

Author

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  • Sunil Kumar Gunda

    (Department of Electrical Engineering, National Institute of Technology, Warangal 506004, India)

  • Venkata Samba Sesha Siva Sarma Dhanikonda

    (Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science, Warangal 506015, India)

Abstract

The discrimination of inrush currents and internal fault currents in transformers is an important feature of a transformer protection scheme. The harmonic current restrained feature is used in conventional differential relay protection of transformers. A literature survey shows that the discrimination between the inrush currents and internal fault currents is still an area that is open to research. In this paper, the classification of internal fault currents and magnetic inrush currents in the transformer is performed by using an extended Kalman filter (EKF) algorithm. When a transformer is energized under normal conditions, the EKF estimates the primary side winding current and, hence, the absolute residual signal (ARS) value is zero. The ARS value will not be equal to zero for internal fault and inrush phenomena conditions; hence, the EKF algorithm will be used for discriminating the internal faults and inrush faults by keeping the threshold level to the ARS value. The simulation results are compared with the theoretical analysis under various conditions. It is also observed that the detection time of internal faults decreases with the severity of the fault. The results of various test cases using the EKF algorithm are presented. This scheme provides fast protection of the transformer for severe faults.

Suggested Citation

  • Sunil Kumar Gunda & Venkata Samba Sesha Siva Sarma Dhanikonda, 2021. "Discrimination of Transformer Inrush Currents and Internal Fault Currents Using Extended Kalman Filter Algorithm (EKF)," Energies, MDPI, vol. 14(19), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6020-:d:640392
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    References listed on IDEAS

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    1. Tao Zheng & Xinhui Yang & Xingchao Guo & Xingguo Wang & Chengqi Zhang, 2020. "Zero-Sequence Differential Current Protection Scheme for Converter Transformer Based on Waveform Correlation Analysis," Energies, MDPI, vol. 13(7), pages 1-14, April.
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    Cited by:

    1. Zhou Ruhan & Nurulafiqah Nadzirah Binti Mansor & Hazlee Azil Illias, 2023. "Identification of Inrush Current Using a GSA-BP Network," Energies, MDPI, vol. 16(5), pages 1-22, February.
    2. Surender Reddy Salkuti, 2022. "Emerging and Advanced Green Energy Technologies for Sustainable and Resilient Future Grid," Energies, MDPI, vol. 15(18), pages 1-7, September.
    3. Łukasz Majka & Bernard Baron & Paweł Zydroń, 2022. "Measurement-Based Stiff Equation Methodology for Single Phase Transformer Inrush Current Computations," Energies, MDPI, vol. 15(20), pages 1-19, October.

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