Publication
PESGM 2014
Conference paper

General bad data identification and estimation in the presence of critical measurement sets

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Abstract

In power systems state estimation, critical sets are groups of measurements whose normalized residuals are (nearly) equal, so that corresponding bad data are not identifiable. A novel methodology for the identification of critical sets and for the estimation of the bad data is introduced, based on a noisy projection of the residuals correlation matrix on a subspace. The proposed solution takes into account model and data uncertainty and is able to detect cases of nearly-critical sets, missed by traditional methods, including higher-order critical k-tuples. A convenient interpretation of the estimated bad data as the total error within the sets is also proposed.

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Publication

PESGM 2014

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