An interpretative structural modeling based network reconfiguration strategy for power systems

Zhang, Can, Sun, Lei, Wen, Fushuan, Lin, Zhenzhi, Ledwich, Gerard, & Xue, Yusheng (2015) An interpretative structural modeling based network reconfiguration strategy for power systems. International Journal of Electrical Power & Energy Systems, 65, pp. 83-93.

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Abstract

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.

Impact and interest:

2 citations in Scopus
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3 citations in Web of Science®

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ID Code: 78591
Item Type: Journal Article
Refereed: Yes
Keywords: Power system restoration, Network reconfiguration, Line importance evaluation, Interpretative structural modeling
DOI: 10.1016/j.ijepes.2014.09.030
ISSN: 0142-0615
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Elsevier Ltd.
Copyright Statement: This is the author’s version of a work that was accepted for publication in International Journal of Electrical Power & Energy Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Electrical Power & Energy Systems, [VOL 65, (2015)] DOI: 10.1016/j.ijepes.2014.09.030
Deposited On: 11 Nov 2014 23:27
Last Modified: 13 Nov 2014 03:52

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