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A Novel Voltage Sag Detection Method Based on a Selective Harmonic Extraction Algorithm for Nonideal Grid Conditions

Author

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  • Zhenyu Li

    (Department of Electrical Engineering, Zhejiang University, No. 38 Zheda Road, Xihu District, Hangzhou 310027, China)

  • Ranchen Yang

    (Department of Electrical Engineering, Zhejiang University, No. 38 Zheda Road, Xihu District, Hangzhou 310027, China)

  • Xiao Guo

    (Department of Electrical Engineering, Zhejiang University, No. 38 Zheda Road, Xihu District, Hangzhou 310027, China)

  • Ziming Wang

    (Department of Electrical Engineering, Zhejiang University, No. 38 Zheda Road, Xihu District, Hangzhou 310027, China)

  • Guozhu Chen

    (Department of Electrical Engineering, Zhejiang University, No. 38 Zheda Road, Xihu District, Hangzhou 310027, China)

Abstract

Voltage sag detection is utilized to capture the sag occurrence moment and calculate the sag depth of power grid voltage in real time, so as to generate reference voltage for controlling voltage interactive equipment such as dynamic voltage restorers (DVRs). However, the traditional voltage sag detection methods based on synchronously rotating frames (SRFs) are unable to acquire high-precision sag information under nonideal grid conditions such as unbalance or harmonic interference. In order to enhance the immunity of the sag detection, a method based on a selective harmonic extraction algorithm (SHEA) is proposed in this paper. Firstly, the state-space model of SHEA is established using discrete orthogonal basis to decouple and separate the signal of target frequency and the signal of interference frequency. The controllability, stability and convergence of SHEA are analyzed theoretically and serve as the criteria for parameter tuning. Moreover, a gain compensator (GC) is used to improve the low and middle frequency gains of the voltage sag detection method based on SHEA so that the dynamic response speed for sag judgment can be optimized quantitatively. The simulation results indicate that the proposed voltage sag detection method has good dynamic and steady-state performance under nonideal power grid conditions such as unbalanced sag, frequency drift, phase variation and harmonic interference.

Suggested Citation

  • Zhenyu Li & Ranchen Yang & Xiao Guo & Ziming Wang & Guozhu Chen, 2022. "A Novel Voltage Sag Detection Method Based on a Selective Harmonic Extraction Algorithm for Nonideal Grid Conditions," Energies, MDPI, vol. 15(15), pages 1-21, July.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5560-:d:876864
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    References listed on IDEAS

    as
    1. Cheng-I Chen & Yeong-Chin Chen & Chung-Hsien Chen & Yung-Ruei Chang, 2020. "Voltage Regulation Using Recurrent Wavelet Fuzzy Neural Network-Based Dynamic Voltage Restorer," Energies, MDPI, vol. 13(23), pages 1-19, November.
    2. Emiyamrew Minaye Molla & Cheng-Chien Kuo, 2020. "Voltage Quality Enhancement of Grid-Integrated PV System Using Battery-Based Dynamic Voltage Restorer," Energies, MDPI, vol. 13(21), pages 1-16, November.
    3. Ali Moghassemi & Sanjeevikumar Padmanaban, 2020. "Dynamic Voltage Restorer (DVR): A Comprehensive Review of Topologies, Power Converters, Control Methods, and Modified Configurations," Energies, MDPI, vol. 13(16), pages 1-38, August.
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    Cited by:

    1. Nhlanhla Mbuli, 2023. "Dynamic Voltage Restorer as a Solution to Voltage Problems in Power Systems: Focus on Sags, Swells and Steady Fluctuations," Energies, MDPI, vol. 16(19), pages 1-26, October.
    2. Jorge De La Cruz & Eduardo Gómez-Luna & Majid Ali & Juan C. Vasquez & Josep M. Guerrero, 2023. "Fault Location for Distribution Smart Grids: Literature Overview, Challenges, Solutions, and Future Trends," Energies, MDPI, vol. 16(5), pages 1-37, February.

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