A Smart Online Over-Voltage Monitoring and Identification System
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-eval...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Molecular Diversity Preservation International
2011
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| Online Access: | http://hdl.handle.net/1721.1/66178 https://orcid.org/0000-0003-2228-2347 |
| Summary: | 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. |
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