LAPSE:2023.32046
Published Article
LAPSE:2023.32046
A Novel Hybrid GWO-LS Estimator for Harmonic Estimation Problem in Time Varying Noisy Environment
Muhammad Abdullah, Tahir N. Malik, Ali Ahmed, Muhammad F. Nadeem, Irfan A. Khan, Rui Bo
April 19, 2023
Abstract
The power quality of the Electrical Power System (EPS) is greatly affected by electrical harmonics. Hence, accurate and proper estimation of electrical harmonics is essential to design appropriate filters for mitigation of harmonics and their associated effects on the power quality of EPS. This paper presents a novel statistical (Least Square) and meta-heuristic (Grey wolf optimizer) based hybrid technique for accurate detection and estimation of electrical harmonics with minimum computational time. The non-linear part (phase and frequency) of harmonics is estimated using GWO, while the linear part (amplitude) is estimated using the LS method. Furthermore, harmonics having transients are also estimated using proposed harmonic estimators. The effectiveness of the proposed harmonic estimator is evaluated using various case studies. Comparing the proposed approach with other harmonic estimation techniques demonstrates that it has a minimum mean square error with less complexity and better computational efficiency.
Keywords
electrical harmonics, grey wolf optimizer, harmonic estimation, total harmonic distortion
Suggested Citation
Abdullah M, Malik TN, Ahmed A, Nadeem MF, Khan IA, Bo R. A Novel Hybrid GWO-LS Estimator for Harmonic Estimation Problem in Time Varying Noisy Environment. (2023). LAPSE:2023.32046
Author Affiliations
Abdullah M: Department of Electrical Engineering, University of Engineering and Technology Taxila, Taxila 47080, Pakistan
Malik TN: Department of Electrical Engineering, HITEC University Taxila, Taxila 47080, Pakistan
Ahmed A: Department of Electrical Engineering, University of Engineering and Technology Taxila, Taxila 47080, Pakistan
Nadeem MF: Department of Electrical Engineering, University of Engineering and Technology Taxila, Taxila 47080, Pakistan; Clean and Resilient Energy Systems (CARES) Research Lab., Texas A&M University, College Station, TX 77553, USA
Khan IA: Clean and Resilient Energy Systems (CARES) Research Lab., Texas A&M University, College Station, TX 77553, USA [ORCID]
Bo R: Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65409, USA
Journal Name
Energies
Volume
14
Issue
9
First Page
2587
Year
2021
Publication Date
2021-05-01
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14092587, Publication Type: Journal Article
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LAPSE:2023.32046
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https://doi.org/10.3390/en14092587
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