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Previous research has justified the use of a state space model for describing smart grid system dynamics. A fault or intrusion in the grid can be found by recognizing a change in system matrices of the state space model. A new hypothesis testing-based approach using the Locally Optimum Unknown Direction (LOUD) test has been proposed to detect possible changes. Previous work has shown that the LOUD...
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)...
This paper studies the distributed change detection problem in Gaussian graphical models (GGMs). Statistical analysis in GGM leads to several advantages, including a smaller number of parameters to model a large scale distribution, less samples required for the detection, faster detection and less communication costs. We formulate the hypothesis testing problem for change detection in GGMs and propose...
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