2022
DOI: 10.1109/access.2022.3149103
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Online Detection of Out-of-Step Condition Using PMU-Determined System Impedances

Abstract: This paper presents a robust and adaptive out-of-step (OOS) protection algorithm, using wide-area information, that can be applied on tie-lines in observable power systems. The developed algorithm is based upon real-time computation of the system impedance and makes use of the wellknown power-angle characteristic. In this way, a setting-less OOS concept in real-time environment is developed, which is applicable for tie-lines in an arbitrary power system. Furthermore, the developed protection algorithm is insta… Show more

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Cited by 11 publications
(5 citation statements)
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References 31 publications
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“…[127] This approach can identify an OOS state more accurately and reliably, with a smaller probability of false alarms or missed detection. [128] This proposed algorithm provides faster tripping (up to 200 ms) than traditional impedance-based OOS methods, making it more reliable.…”
Section: Ref Nomentioning
confidence: 95%
“…[127] This approach can identify an OOS state more accurately and reliably, with a smaller probability of false alarms or missed detection. [128] This proposed algorithm provides faster tripping (up to 200 ms) than traditional impedance-based OOS methods, making it more reliable.…”
Section: Ref Nomentioning
confidence: 95%
“…In [96], on the contrary, PMU data are used to refine resistance measurements, which leads to an increase in the quality of automation. In [97,98], approaches to improving the AESM installed on the generator are proposed. In the first case, the PMU data are used to improve the quality of work relative to the traditional approach to determining asynchronous running, reminiscent of ECS algorithms.…”
Section: Phasor Measurements and Aesmmentioning
confidence: 99%
“…OOS detection based on PMU-determined impedances [16] The method is more secure and provides faster OOS detection than conventional solutions.…”
Section: Proposed Approachmentioning
confidence: 99%