DocumentCode :
252112
Title :
Optimal PMU placement for identification of multiple power line outages in smart grids
Author :
Jie Wu ; Jinjun Xiong ; Shil, Prasenjit ; Yiyu Shi
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
fYear :
2014
fDate :
3-6 Aug. 2014
Firstpage :
354
Lastpage :
357
Abstract :
Placing appropriate numbers of PMUs is critical to collect phase angle data for best identifying multiple line outages in wide-area transmission system, because of high deployment costs. This work focuses on exploring the global optimal strategy of PMU deployment for maximizing the average identification capability of multiple line outages. Inspired by Kullback-Leibler (KL) distance, this paper proposes the closed-form mathematical model to describe the average identification capability of multiple simultaneous line outages. Using IEEE 14-bus system, the optimal trade-off between the average identification capability and the number of PMUs is characterized. The proposed model successfully portrays the statistical identification performance of multiple line outages. The numerical result shows that the global optimal PMU placement algorithm has higher average identification capability when compared to the random PMU placement algorithm.
Keywords :
mathematical analysis; phasor measurement; smart power grids; statistical analysis; IEEE 14-bus system; KL distance; Kullback-Leibler distance; average identification capability; closed-form mathematical model; multiple power line outage identification; optimal PMU placement; smart grids; statistical identification performance; wide-area transmission system; Conferences; Mathematical model; Numerical models; Optimization; Phasor measurement units; Smart grids; Vectors; Multiple line outages; average identification capability; dissimilarity distance; number of PMUs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (MWSCAS), 2014 IEEE 57th International Midwest Symposium on
Conference_Location :
College Station, TX
ISSN :
1548-3746
Print_ISBN :
978-1-4799-4134-6
Type :
conf
DOI :
10.1109/MWSCAS.2014.6908425
Filename :
6908425
Link To Document :
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