Incipient Fault Prediction in Power Quality Monitoring

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CIRED 2019 - 1535.pdf (311.42 KB)

Paper number

1535

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Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

Hoffmann, Volker, SINTEF AS, Norway
Michałowska, Katarzyna, SINTEF AS, Norway
Andresen, Christian, SINTEF Energy Research AS, Norway
Torsæter, Bendik Nybakk, SINTEF Energy Research AS, Norway

Abstract

European and global power grids are moving towards a Smart Grid architecture. Supporting this, advanced measurement equipment such as PQAs and PMUs are being deployed. These generate vast amounts of data upon which machine learning models capable of forecasting incipient faults can be built. We use live measurements from nine PQA nodes in the Norwegian grid to predict incipient interruptions, voltage dips, and earth faults. After training ensembles of gradient boosted decision trees on spectral decompositions of cycle-by-cycle voltage measurements, we evaluate their predictive performance. We find that interruptions are easiest to predict (95 % true positive, 20 % false positives). Earth faults and voltage dips are more challenging. Our models outperform naïve classifiers. We have explored forecast horizons of up to 40 seconds, but we have indications that forecast horizons of at least a few minutes are feasible.

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Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/444
http://dx.doi.org/10.34890/673

ISSN

2032-9644

ISBN

978-2-9602415-0-1