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Bad data pre-filter for state estimation
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DOI：10.1016/j.ijepes.2010.06.016.png)
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Abstract
En 中文
Systematic approach for pre-filter for state estimation based on wavelet analysis to detect and eliminate bad data, is developed in this work. Unbiased (random/Gaussian) bad data such as, transient meter failures, transient meter malfunction, and measurements captured during system transients, are inherently in the form of large abrupt change of short duration in a measurement-sequence. These should be detected in pre-filtering stage because their presence poses an extra burden on post-SE bad data analysis. The test results of the proposed pre-filter on two test systems establish that there is a significant reduction in the number of iterations required for bad data detection and elimination. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords:
Bad data detection
Discrete wavelet transform
State estimation
Journal
I
IF:
5
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1.1W
Citations:
3.1W