Journal
IEEE ACCESS
Volume 8, Issue -, Pages 146807-146830Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3014732
Keywords
Power quality; Monitoring; Renewable energy sources; Feature extraction; Wavelet analysis; Wavelet packets; Wavelet domain; Artificial intelligence; power quality disturbances; international standards of power quality monitoring; signal processing; renewable energy sources; noise
Categories
Funding
- Danida Mobility Grant [19-MG04AAU]
- Visvesvaraya PhD Scheme, MeitY, India [AKT/2014/0030]
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The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area.
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