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A PMU-Based Method for Smart Transmission Grid Voltage Security Visualization and Monitoring

Author

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  • Heng-Yi Su

    (Department of Electrical Engineering, Feng Chia University (FCU), No. 100, Wenhwa Road, Seatwen, Taichung 40724, Taiwan)

  • Tzu-Yi Liu

    (Department of Electrical Engineering, Feng Chia University (FCU), No. 100, Wenhwa Road, Seatwen, Taichung 40724, Taiwan)

Abstract

With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading margin using PMU data from a wide-area monitoring system (WAMS) to construct the voltage stability boundary (VSB) of a transmission grid. Specifically, a new approach for online loading margin estimation that considers system load trends is proposed based on the Thevenin equivalent (TE) technique and the Mobius transformation (MT) technique. A VSB is then computed by means of real-time PMU measurements and is presented in a complex load power space. VSB can be utilized as a visualization tool that is able to provide real-time visualization of the current voltage stability situation. The proposed method is fast and adequate for online voltage security assessment. Furthermore, it enables us to significantly increase a system operator’s situational awareness for operational decision making. Simulation studies were carried out using different sized power grid models under various operating conditions. The simulation results are shown to validate the capability of the proposed method.

Suggested Citation

  • Heng-Yi Su & Tzu-Yi Liu, 2017. "A PMU-Based Method for Smart Transmission Grid Voltage Security Visualization and Monitoring," Energies, MDPI, vol. 10(8), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1103-:d:106126
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    References listed on IDEAS

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    1. Weisi Deng & Buhan Zhang & Hongfa Ding & Hang Li, 2017. "Risk-Based Probabilistic Voltage Stability Assessment in Uncertain Power System," Energies, MDPI, vol. 10(2), pages 1-19, February.
    2. Tiankui Sun & Zhimin Li & Shuang Rong & Jian Lu & Weixing Li, 2017. "Effect of Load Change on the Thevenin Equivalent Impedance of Power System," Energies, MDPI, vol. 10(3), pages 1-6, March.
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    Cited by:

    1. Jiang Li & Wenzhen Wei & Shuo Zhang & Guoqing Li & Chenghong Gu, 2018. "Conditional Maximum Likelihood of Three-Phase Phasor Estimation for μPMU in Active Distribution Networks," Energies, MDPI, vol. 11(5), pages 1-18, May.
    2. Do-In Kim, 2021. "Complementary Feature Extractions for Event Identification in Power Systems Using Multi-Channel Convolutional Neural Network," Energies, MDPI, vol. 14(15), pages 1-15, July.
    3. Heng-Yi Su & Tzu-Yi Liu, 2017. "GECM-Based Voltage Stability Assessment Using Wide-Area Synchrophasors," Energies, MDPI, vol. 10(10), pages 1-16, October.
    4. Anan Zhang & Huang Huang & Wei Yang & Hongwei Li, 2019. "Multivariable Regression Equivalent Model of Interconnected Active Distribution Networks Based on Boundary Measurement," Energies, MDPI, vol. 12(12), pages 1-17, June.

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