Application of Robust PCA with a structured outlier matrix to topology estimation in power grids

Chrétien, Stéphane and Clarkson, Paul and Garcia, Maria Segovia (2018) Application of Robust PCA with a structured outlier matrix to topology estimation in power grids. International Journal of Electrical Power and Energy Systems, 100. pp. 559-564. ISSN 0142-0615 (https://doi.org/10.1016/j.ijepes.2018.02.003)

[thumbnail of Chretien-etal-IJEPES-2018-Application-of-Robust-PCA-with-a-structured-outlier-matrix]
Preview
Text. Filename: Chretien_etal_IJEPES_2018_Application_of_Robust_PCA_with_a_structured_outlier_matrix.pdf
Accepted Author Manuscript
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo

Download (420kB)| Preview

Abstract

Robust PCA is a widely used technique for Principal Component Analysis when the data is corrupted by outliers. The goal of the present short note is to report on the performance results of a simple modification of the method of Netrapali et al. for estimating Low Rank + Sparse models where the sparse matrix has the structure of a tree. We demonstrate the efficiency of the approach on the problem of estimating the topology in power grid networks.