Identification of Power Quality Issues using Kalman Filter

S  Rudhra  and M  Gopikrishnan   nbsp

doi:10.17485/ijst/2015/v8i32/87502

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Identification of Power Quality Issues using Kalman Filter

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i32/87502

Year: 2015, Volume: 8, Issue: 32, Pages: 1-5

Original Article

Identification of Power Quality Issues using Kalman Filter

S. Rudhra¹ and M. Gopikrishnan^2*

¹Department of Electrical and Electronics Engineering, Jerusalem College of Engineering, Velachery Main Road, Narayanpuram, Pallikaranai, Chennai – 600100, Tamil Nadu, India; [email protected]
² Department of Electrical and Electronics Engineering, Bharath University, Agharam Road, Selaiyur, Chennai – 600073, Tamil Nadu, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

AKalman filter - generalized regression neural network based technique for the classification of power quality disturbances is presented here. A two stage classifier is proposed in which feature extraction is performed using a Kalman filter. Amplitude of the waveforms is the feature extracted from the Kalman filter and given as input to generalized regression neural network which classifies power quality disturbances. Distored waveforms on the power system model were simulated using Matlab software. Five classes of PQ disturbances were classified and the performance evaluation has been done using 500 signals, with a sampling rate of 128 per cycle of each signal.
Keywords: Kalman Filter, Neural Network, Power Quality, Power Quality Disturbances