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A sequential testing framework for identifying a transmission line outage in a power system

Kumar, KC and Gurrala, G and Sundaresan, R (2019) A sequential testing framework for identifying a transmission line outage in a power system. In: 10th ACM International Conference on Future Energy Systems, e-Energy 2019, 25 June 2019-28 June 2019, Phoenix, pp. 331-342.

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Official URL: https://doi.org/10.1145/3307772.3328297


The topology of a power system changes when a line outage is encountered. Identifying which line has failed in the shortest possible time is of importance due to the cascading nature of such failures. In this work, we propose a state estimation based sequential hypothesis testing procedure to locate the failed line.We focus on single line outages as these are the most frequently occurring failures. Earlier work on state estimation based sequential testing procedure used a DC approximation model assuming that the sensors provided angle and voltage information. This is known to be a coarse model but results in a simpler linear estimation problem. In this work, we look at a finer nonlinear model of power measurements and treat phase angles and voltages as hidden states. After a local linearization, we propose a Kalman filter based state estimation followed by a generalized likelihood ratio testing procedure to determine which of the lines has failed. We consider both centralized and decentralized approaches. In the centralized case, measurements from every installed meter is made available to the system operator. In the decentralized case, only limited aggregated information is made available because of, for example, communication capacity constraints. We test our algorithms on the IEEE 14 and 118 bus systems and show that all high risk link failures are quickly identified. © 2019 Association for Computing Machinery.

Item Type: Conference Paper
Publication: e-Energy 2019 - Proceedings of the 10th ACM International Conference on Future Energy Systems
Publisher: Association for Computing Machinery, Inc
Additional Information: The copyright for this article belongs to Association for Computing Machinery, Inc
Keywords: Aggregates; Electric power transmission; Kalman filters; Smart power grids; State estimation; Topology, Decentralized state estimation; Kalman-filtering; Sequential hypothesis testing; Topology identification; Unscented Kalman Filter, Outages
Department/Centre: Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Division of Electrical Sciences > Electrical Engineering
Date Deposited: 23 Dec 2022 05:16
Last Modified: 23 Dec 2022 05:16
URI: https://eprints.iisc.ac.in/id/eprint/78519

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