A Smart Online Over-Voltage Monitoring and Identification System
Author(s)
Wang, Jing; Yang, Qing; Sima, Wenxia; Yuan, Tao; Zahn, Markus
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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.
Date issued
2011-04Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. High Voltage Research Laboratory; Massachusetts Institute of Technology. Laboratory for Electromagnetic and Electronic Systems; Massachusetts Institute of Technology. Research Laboratory of ElectronicsJournal
Energies
Publisher
Molecular Diversity Preservation International
Citation
Wang, Jing et al. “A Smart Online Over-Voltage Monitoring and Identification System.” Energies 4 (2011): 599-615. © 2011 by the authors
Version: Author's final manuscript
ISSN
1996-1073