NDLI: A Static State Estimation Approach Including Bad Data Detection and Identification in Power Systems

Content Provider	IEEE Xplore Digital Library
Author	Jeu-Min Lin Heng-Yau Pan
Copyright Year	2007
Description	Author affiliation: Dept. of Electr. Eng., Far East Univ., Tainan (Jeu-Min Lin; Heng-Yau Pan)
Abstract	This paper presents an efficient method for power system static state estimation along with a statistical technique of bad data detection and identification. In the estimation process, the exponential function is utilized to modify the variances of measurements in anticipation of maintaining the estimation performance under the bad data scenario. Besides, with the aid of the proposed gap statistic method, those bad data can be effectively detected and identified from the set of raw measurements. To validate the effectiveness of the proposed approach, this method has been tested under different simulated scenarios. Test results help confirm the feasibility of the method for the applications considered.
Starting Page	1
Ending Page	7
File Size	249001
Page Count	7
File Format	PDF
ISBN	142441296X
ISSN	19325517
DOI	10.1109/PES.2007.385500
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	State estimation Power systems Power system measurements Statistics Testing Power system simulation Measurement errors Neural networks Covariance matrix Measurement units gap statistic method Static state estimation bad data detection and identification
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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