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Identification et caractérisation des perturbations affectant les réseaux électriques HTA.

Abstract : The recognition of disturbances affecting MV networks is essential to industrials and distribution system operators. The aim of this thesis work is to design a near real-time automatic system able to detect and identify disturbances from their waveforms. Segmentation methods split the disturbed waveforms into transient and steady-state intervals. They use Kalman filters or anti-harmonic filters to extract the transient intervals. Adaptive thresholding methods increase the detection capacity while a posterior delay compensation methods improve the accuracy of the decomposition. Indicators adapted to the disturbance dynamic are used to characterize its steady-state and transient phases. They are robust to segmentation inaccuracies as well as to steady-state disturbances such as harmonics. Two distinct decision systems are also studied: expert recognition systems and SVM classifiers. During the learning stage, a large simulated event database is used to train both systems. Their performances are evaluated on real events: the type and direction of the measured disturbances are determined with a recognition rate over 98%.
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Submitted on : Wednesday, February 27, 2013 - 4:57:37 PM
Last modification on : Monday, December 14, 2020 - 12:38:06 PM
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  • HAL Id : tel-00650911, version 2



Mathieu Caujolle. Identification et caractérisation des perturbations affectant les réseaux électriques HTA.. Autre. Supélec, 2011. Français. ⟨NNT : 2011SUPL0008⟩. ⟨tel-00650911v2⟩



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