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Change detection in smart grids using errors in variables models

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3 Author(s)
Chuanming Wei ; Lehigh University, USA ; Ami Wiesel ; Rick S. Blum

We consider fault detection through apparent changes in the bus susceptance parameters of modern power grids. We formulate the problem using a linear errors-invariables model and derive its corresponding generalized likelihood ratio (GLRT) based on the total least squares (TLS) methodology. Next, we propose a competing detection technique based on the recently proposed total maximum likelihood (TML) framework. We derive the so called TML-GLRT, and show that it can be interpreted as a regularized TLS-GLRT. Numerical simulations in a noisy smart grid setting illustrate the advantages of TML-GLRT over TLS-GLRT with no additional computational costs.

Published in:

Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th

Date of Conference:

17-20 June 2012