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A Fixed Length Adaptive Moving Average Filter-Based Synchrophasor Measurement Algorithm for P Class PMUs

Author

Listed:
  • Hui Xue

    (College of Information and Electrical Engineering, China Agricultural University, 100083 Beijing, China)

  • Mengjie Ruan

    (College of Information and Electrical Engineering, China Agricultural University, 100083 Beijing, China)

  • Yifan Cheng

    (College of Information and Electrical Engineering, China Agricultural University, 100083 Beijing, China)

Abstract

Accurate and fast synchrophasor measurement is the key to the wide applications of PMUs in the system-wide monitoring and reliable operation of smart grid. To address this issue, a fixed length moving average filter-based synchrophasor measurement algorithm for P class phasor measurement units (PMUs) (FA-PSMA) is proposed in this paper. Firstly, a novel fixed length adaptive moving average filter (FAMAF) is proposed. The FAMAF has an adaptive filter capability with a fixed data window length. Then, the FAMAF is applied after a phase-locked loop (PLL) for enhanced disturbance rejection capability under frequency drifts. Finally, a detailed performance assessment is presented to validate the performance of the proposed FA-PSMA. Theoretical analysis and simulation results validate that the proposed FA-PSMA can track the grid frequency and phasor accurately under distorted grid conditions. The response time and measurement accuracy satisfy the requirements specified in IEC/IEEE 60255-118-1.

Suggested Citation

  • Hui Xue & Mengjie Ruan & Yifan Cheng, 2019. "A Fixed Length Adaptive Moving Average Filter-Based Synchrophasor Measurement Algorithm for P Class PMUs," Energies, MDPI, vol. 12(21), pages 1-14, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:21:p:4168-:d:282369
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    Cited by:

    1. Malgorzata Binek & Andrzej Kanicki & Pawel Rozga, 2021. "Application of an Artificial Neural Network for Measurements of Synchrophasor Indicators in the Power System," Energies, MDPI, vol. 14(9), pages 1-14, April.

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