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A Smart Online Over-Voltage Monitoring and Identification System

Author

Listed:
  • Jing Wang

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China)

  • Qing Yang

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China
    Research Laboratory of Electronics, Laboratory for Electromagnetic and Electronic Systems, High Voltage Research Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA)

  • Wenxia Sima

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China)

  • Tao Yuan

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China)

  • Markus Zahn

    (Research Laboratory of Electronics, Laboratory for Electromagnetic and Electronic Systems, High Voltage Research Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA)

Abstract

This paper proposes a complete and effective smart over-voltage monitoring and identification system. In recent years, smart grids are of the greatest interest in power system research. One of the main features of smart grid is their self-healing, which can continuously carry out online self-evaluation, discover existing faults, and correct them immediately. The over-voltage smart monitoring-identification-suppression systems play a key role in the construction of self-healing grids. In this paper, eight kinds of common over-voltage are discussed and analyzed. The S-transform algorithm is used to extract features of over-voltage. Aiming at the main features of each kind of over-voltage, six different characteristic quantities are proposed. A well designed fuzzy expert system and a support vector machine are employed as the classifiers to build a two-step identification model. The accuracy of the identification system is verified by field records. Results show that this system is feasible and promising for real applications.

Suggested Citation

  • Jing Wang & Qing Yang & Wenxia Sima & Tao Yuan & Markus Zahn, 2011. "A Smart Online Over-Voltage Monitoring and Identification System," Energies, MDPI, vol. 4(4), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:4:y:2011:i:4:p:599-615:d:12093
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    Citations

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    Cited by:

    1. Qing Yang & Jing Wang & Wenxia Sima & Lin Chen & Tao Yuan, 2011. "Mixed Over-Voltage Decomposition Using Atomic Decompositions Based on a Damped Sinusoids Atom Dictionary," Energies, MDPI, vol. 4(9), pages 1-18, September.
    2. Qing Yang & Peiyu Su & Yong Chen, 2017. "Comparison of Impulse Wave and Sweep Frequency Response Analysis Methods for Diagnosis of Transformer Winding Faults," Energies, MDPI, vol. 10(4), pages 1-16, March.
    3. Kaihua Jiang & Lin Du & Huan Chen & Feng Yang & Yubo Wang, 2019. "Non-Contact Measurement and Polarity Discrimination-Based Identification Method for Direct Lightning Strokes," Energies, MDPI, vol. 12(2), pages 1-17, January.
    4. Xingliang Jiang & Yunfeng Xia & Jianlin Hu & Zhijin Zhang & Lichun Shu & Caxin Sun, 2011. "An S-Transform and Support Vector Machine (SVM)-Based Online Method for Diagnosing Broken Strands in Transmission Lines," Energies, MDPI, vol. 4(9), pages 1-23, August.
    5. Qing Yang & Bo Zhang & Jiaquan Ran & Song Chen & Yanxiao He & Jian Sun, 2017. "Measurement of Line-to-Ground Capacitance in Distribution Network Considering Magnetizing Impedance’s Frequency Characteristic," Energies, MDPI, vol. 10(4), pages 1-14, April.
    6. Lin Chen & Qing Yang & Jing Wang & Wenxia Sima & Tao Yuan, 2011. "Classification of Fundamental Ferroresonance, Single Phase-to-Ground and Wire Breakage Over-Voltages in Isolated Neutral Networks," Energies, MDPI, vol. 4(9), pages 1-20, August.
    7. Arends, Marcel & Hendriks, Paul H.J., 2014. "Smart grids, smart network companies," Utilities Policy, Elsevier, vol. 28(C), pages 1-11.

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