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Energies 2011, 4(4), 599-615; doi:10.3390/en4040599
Article

A Smart Online Over-Voltage Monitoring and Identification System

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Received: 24 February 2011; in revised form: 6 April 2011 / Accepted: 15 April 2011 / Published: 18 April 2011
(This article belongs to the Special Issue Future Grid)
Download PDF [381 KB, uploaded 18 April 2011]
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.
Keywords: smart grid; over-voltage; identification; S-transform; fuzzy expert system smart grid; over-voltage; identification; S-transform; fuzzy expert system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Wang, J.; Yang, Q.; Sima, W.; Yuan, T.; Zahn, M. A Smart Online Over-Voltage Monitoring and Identification System. Energies 2011, 4, 599-615.

AMA Style

Wang J, Yang Q, Sima W, Yuan T, Zahn M. A Smart Online Over-Voltage Monitoring and Identification System. Energies. 2011; 4(4):599-615.

Chicago/Turabian Style

Wang, Jing; Yang, Qing; Sima, Wenxia; Yuan, Tao; Zahn, Markus. 2011. "A Smart Online Over-Voltage Monitoring and Identification System." Energies 4, no. 4: 599-615.


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