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Method for Estimating Harmonic Parameters Based on Measurement Data without Phase Angle

Author

Listed:
  • Fulin Zhou

    (School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Feifan Liu

    (School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Ruixuan Yang

    (School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Huanrui Liu

    (Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China)

Abstract

The excessive use of power electronics makes power quality problems in power grids increasingly prominent. The estimation of the harmonic parameters of harmonic sources in the power grid and the division of harmonic responsibilities are of great significance for the evaluation of power quality. At present, methods for estimating harmonic parameters and harmonic responsibilities need to provide the amplitude and phase information of the current and voltage of the point of common coupling (PCC). However, in practical engineering applications, the general power quality monitor only provides the amplitude information of the voltage and current of the measured point and the phase difference information between them. Missing phase information invalidates existing methods. Based on the partial least squares regression method, the present work proposes a method for estimating harmonic parameters in the case of monitoring data without phase. This method only needs to measure the amplitude information of the harmonic voltage and current of the PCC and the phase difference between them, then use the measurable data to estimate the harmonic parameters and the harmonic responsibility of each harmonic source. It provides a new way to effectively solve the problem that the measured data of the project has no phase information. The feasibility and effectiveness of the proposed method are proved by simulation data and measured engineering data.

Suggested Citation

  • Fulin Zhou & Feifan Liu & Ruixuan Yang & Huanrui Liu, 2020. "Method for Estimating Harmonic Parameters Based on Measurement Data without Phase Angle," Energies, MDPI, vol. 13(4), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:879-:d:321493
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    Citations

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    Cited by:

    1. Ruixuan Yang & Fulin Zhou & Kai Zhong, 2020. "A Harmonic Impedance Identification Method of Traction Network Based on Data Evolution Mechanism," Energies, MDPI, vol. 13(8), pages 1-15, April.
    2. Denis Sidorov & Fang Liu & Yonghui Sun, 2020. "Machine Learning for Energy Systems," Energies, MDPI, vol. 13(18), pages 1-6, September.
    3. Qiujiang Liu & Binghan Sun & Qinyao Yang & Mingli Wu & Tingting He, 2020. "Harmonic Overvoltage Analysis of Electric Railways in a Wide Frequency Range Based on Relative Frequency Relationships of the Vehicle–Grid Coupling System," Energies, MDPI, vol. 13(24), pages 1-16, December.

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