2019
DOI: 10.1109/tia.2019.2921260
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Compressive System Identification for Multiple Line Outage Detection in Smart Grids

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Cited by 25 publications
(11 citation statements)
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“…Nevertheless, these methods are highly dependent on prior knowledge of the topology configuration. Notably, for the same purpose, expectation-maximization-based technique is proposed by Yu et al [11], and sparse recovery-based techniques are proposed by Jafarian et al [12] and Babakmehr et al [13], while the data-driven techniques are also reported by Dua et al [14].…”
Section: A Related Workmentioning
confidence: 99%
“…Nevertheless, these methods are highly dependent on prior knowledge of the topology configuration. Notably, for the same purpose, expectation-maximization-based technique is proposed by Yu et al [11], and sparse recovery-based techniques are proposed by Jafarian et al [12] and Babakmehr et al [13], while the data-driven techniques are also reported by Dua et al [14].…”
Section: A Related Workmentioning
confidence: 99%
“…When conventional grids must be turned into intelligent grids, adaptive approaches must be built to achieve the optimum network for the output of the smart grid features. Graph theory theories are often used to determine the best network model and topological framework enabling an intelligent grid [6]. Intellections, computing technology and automatic control systems are the three main elements of the cognitive network [15], [18].…”
Section: Smart Grids -Basicsmentioning
confidence: 99%
“…Finally, a regularized least square method is used to solve the model and to estimate the locations of lines that are under outage. [21] considered the power network as a single graph and initialized the mathematical formulation of the power line outage detection problem using the DC power flow model. Then, a sparse representation-based formulation is applied for this problem.…”
Section: Introductionmentioning
confidence: 99%