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Ensemble approach for automated extraction of critical events from mixed historical PMU data sets

: Kummerow, Andre; Nicolai, Steffen; Bretschneider, Peter

Postprint urn:nbn:de:0011-n-5251172 (766 KByte PDF)
MD5 Fingerprint: e3d952496934daf46f2aba4410e40a9d
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Erstellt am: 18.1.2019

Institute of Electrical and Electronics Engineers -IEEE-:
IEEE Power & Energy Society General Meeting, PESGM 2018 : 5-10 August 2018, Portland, Oregon, USA
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-7703-2
ISBN: 978-1-5386-7702-5
ISBN: 978-1-5386-7704-9
5 S.
Institute of Electrical and Electronics Engineers, Power and Energy Society (IEEE PES General Meeting) <2018, Portland/Or.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

The scope of this survey is the automated extraction of critical events from mixed PMU data sets without prior knowledge about existing failure patterns. An unsupervised procedure is introduced that identifies arbitrary disturbance types (e.g. voltage sags, frequency drops, oscillations) using an ensemble outlier detection approach. For that, different techniques for signal analysis are used to generate features in time and frequency domain. That approach enables the exploration of critical grid dynamics in power systems. Furthermore new failure patterns can be extracted for the creation of training datasets used for online detection algorithms.