DocumentCode
22862
Title
Towards an Auto-Associative Topology State Estimator
Author
Krstulovic, Jakov ; Miranda, V. ; Simoes Costa, Antonio J. A. ; Pereira, J.
Author_Institution
TEC (Technol. & Sci.), INESC, Porto, Portugal
Volume
28
Issue
3
fYear
2013
fDate
Aug. 2013
Firstpage
3311
Lastpage
3318
Abstract
This paper presents a model for breaker status identification and power system topology estimation based on a mosaic of local auto-associative neural networks. The approach extracts information from values of the analog electric variables and allows the recovery of missing sensor signals or the correction of erroneous data about breaker status. The results are confirmed by extensive tests conducted on an IEEE benchmark network.
Keywords
circuit breakers; network topology; neural nets; power system management; IEEE benchmark network; analog electric variables; auto-associative topology; breaker status identification; neural networks; power system topology estimation; sensor signals; state estimator; Data models; Network topology; Optimization; Pollution measurement; State estimation; Topology; Training; Autoencoders; neural networks; power system topology; state estimation;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2012.2236656
Filename
6416996
Link To Document