Empirical Mode Decomposition with Wavelet Transform Based Analytic Signal for Power Quality Assessment
Abstract:This paper proposes empirical mode decomposition
(EMD) together with wavelet transform (WT) based analytic signal
for power quality (PQ) events assessment. EMD decomposes the
complex signals into several intrinsic mode functions (IMF). As
the PQ events are non stationary, instantaneous parameters have
been calculated from these IMFs using analytic signal obtained
form WT. We obtained three parameters from IMFs and then used
KNN classifier for classification of PQ disturbance. We compared
the classification of proposed method for PQ events by obtaining
the features using Hilbert transform (HT) method. The classification
efficiency using WT based analytic method is 97.5% and using HT
based analytic signal is 95.5%.
 R. A. Flores, ”State of the art in the classification of power quality events,
an overview. In Harmonics and Quality of Power, 2002. 10th International
Conference on (vol. 1, pp. 17-20) IEEE, 2002.
 M. V. Chilukuri and P. K. Dash, ”Multiresolution S-transform-based fuzzy
recognition system for power quality events”, IEEE Transactions on Power
Delivery, vol. 19, no. 1, pp. 323-330, 2004.
 A. M. Gargoom, N. Ertugrul and W. L. Soong, ”Investigation of effective
automatic recognition systems of power-quality events”, IEEE Transactions
on Power Delivery, vol. 22, no. 4, pp. 2319-2326, 2007.
 S. Mishra, C. N. Bhende and B. K. Panigrahi, ”Detection and
classification of power quality disturbances using S-transform and
probabilistic neural network”, IEEE transactions on power delivery, vol.
23, no. 1, pp. 280-287, 2008.
 J. H. Han, G. Jan and C. H. Park, ”Probabilistic risk assessment for
an optimal selection of voltage sag mitigation devices using stochastic
estimation of voltage sags”, In Advanced Power System Automation
and Protection (APAP), 2011 International Conference on (vol. 3, pp.
1943-1946). IEEE. 2011.
 M. Manjula and A. V. R. S. Sarma, ”Comparison of empirical mode
decomposition and wavelet based classification of power quality events”,
Energy Procedia, 14, pp.1156-1162, 2012.
 C. Aneesh, S. Kumar, P. M. Hisham and K. P. Soman, ”Performance
comparison of variational mode decomposition over empirical wavelet
transform for the classification of power quality disturbances using support
vector machine”, Procedia Computer Science, 46, pp.372-380, 2015
 M. K. Saini and K. Dhamija, ”Application of Hilbert-Huang Transform
in the field of power quality events analysis”, In Proc. of Int. Conf. on
Advances in Signal Processing and Communication, pp. 118-124, 2013.
 M. V. Reddy and R. Sodhi, ”A modified S-transform and random
forests-based power quality assessment framework”, IEEE Transactions
on Instrumentation and Measurement, vol. 67, no. 1, pp. 78-89, 2018.
 S. Shukla, S. Mishra and B. Singh, ”Power quality event classification
under noisy conditions using EMD-based de-noising techniques”, IEEE
Transactions on industrial informatics, vol. 10, no. 2, pp. 1044-1054, 2014.
 S. Shukla, S. Mishra and B. Singh, ”Empirical-mode decomposition
with Hilbert transform for power-quality assessment”, IEEE transactions
on power delivery, vol. 24, no. 4, pp. 2159-2165, 2009.
 J. Huang and Z. Jiang, ”Power Quality Assessment of Different Load
Categories”, Energy Procedia, 141, pp.345-351, 2017.
 A. Pavas and C. Garzon, ”Causality assessment for power quality
stationary disturbances”, In Innovative Smart Grid Technologies
Conference Europe (ISGT-Europe), 2014 IEEE PES, pp. 1-7, 2014.
 S. Roy and S. Nath, ”Classification of power quality disturbances
using features of signals”, International Journal of Scientific and Research
Publications, vol. 2, no. 11, pp. 1-9, 2012.
 S. Chattopadhyay, S. Sengupta and M. Mitra, ”Area-based approach
in power quality assessment”, Advances in Power Electronics, Article ID
147359, pp. 1-6, 2008.
 J. Barros, M. D. Apraiz and R. I. Diego, ”On-line monitoring of
electrical power quality for assessment of induction motor performance”, In
Electric Machines and Drives Conference, IEMDC’09. IEEE International,
pp. 1140-1145, 2009.
 D. De Yong, S. Bhowmik and F. Magnago, Optimized Complex Power
Quality Classifier Using One vs. Rest Support Vector Machines. Energy
and Power Engineering, 9, pp. 568-587, 2017.
 Jinghuai Gao, XiaolonG Dong, Wen Bing Wang, Youming Li and
Cunhan Pan, ”Instantaneous parameter extraction via wavelet transform”,
IEEE Trans. on Geoscience and Remote Sensings, vol. 37, no.2 March