A Smart Online Over-Voltage Monitoring and Identification System

Jing Wang, Qing Yang, Wenxia Sima, Tao Yuan and Markus Zahn
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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
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

Energies, 2011, vol. 4, issue 4, 1-17

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 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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