NDLI: Design of an automated system for detection and classification of power quality disturbances

Content Provider	IEEE Xplore Digital Library
Author	MoeinDarbari, M. Pourreza, H. Monfared, M.
Copyright Year	2015
Description	Author affiliation: Comput. Eng. Dept., Ferdowsi Univ., Mashhad, Iran (MoeinDarbari, M.; Pourreza, H.) \|\| Electr. Eng. Dept., Ferdowsi Univ., Mashhad, Iran (Monfared, M.)
Abstract	Power quality (PQ) is one of the most significant issues in power monitoring systems and smart grids in recent years. Identifying disturbances has an important role in improving PQ. The intention of this paper is to improve the accuracy of the detection step in PQ disturbances. To do so an adaptive method called CEEMD (complete ensemble empirical mode decomposition) is used here for the first time. Here a new modified version of Hilbert Huang Transform (HHT) has been proposed for feature extraction. This version is combination of CEEMD and Hilbert Transform. The performance of the proposed method is compared with classical algorithms like HHT and MHHT (Modified HHT). Experimental results demonstrate the efficiency of the proposed method.
Starting Page	181
Ending Page	186
File Size	2513162
Page Count	6
File Format	PDF
ISBN	9781467392808
DOI	10.1109/ICCKE.2015.7365824
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-29
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gaussian noise Power quality Disturbance Intrinsic mode functions (IMFs) Discrete wavelet transforms Yttrium Noise measurement Mathematical model Mode decomposition
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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