Hybrid Weighted Least Square Multi-Verse Optimizer (WLS–MVO) Framework for Real-Time Estimation of Harmonics in Non-Linear Loads

Abdul Haseeb, Umar Waleed, Muhammad Mansoor Ashraf, Faisal Siddiq, Muhammad Rafiq () and Muhammad Shafique ()
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Abdul Haseeb: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Umar Waleed: Faculty of Electrical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi 23460, Pakistan
Muhammad Mansoor Ashraf: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Faisal Siddiq: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Muhammad Rafiq: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Muhammad Shafique: Department of Civil and Environmental Engineering, Brunel University London, Uxbridge UB8 3PH, UK

Energies, 2023, vol. 16, issue 2, 1-15

Abstract: The electric power quality has become a serious concern for electric utilities and end users owing to its undesirable effects on system capabilities and performance. Harmonic levels on power systems have been pronounced to a greater extent with the continuous growth in the application of solid-state and reactive power compensatory devices. Harmonics are the key constituents that are mainly responsible for power quality deterioration. Power system harmonics need to be correctly estimated and filtered to increase power quality. This research work focuses on accurate estimation of power system harmonics with the proposed hybrid weighted least-square multi-verse optimizer (WLS–MVO) based framework. Multi-verse optimizer replicates the phenomenon of the formation of new universes as described by multi-verse theory to solve complex real-world optimization problems. The proposed WLS–MVO framework is tested and validated by estimating the harmonics present in multiple test signals with different noise levels. Amplitudes and phases of harmonics present in the polluted signal were estimated, and the framework computational time was compared with the previously developed technique’s results which are reported in the literature. There was 80% reduction in computational time and 82% improvement in terms of accuracy in estimating harmonics using WLS–MVO as compared to previously developed techniques. The performance of the developed framework is further validated by estimating the harmonics present in the real-time voltage and current waveforms obtained from axial flux permanent magnet generator (AFPMSG), uninterruptible power supply (UPS), and light-emitting diode (LED). The purposed technique technique outperforms the already-developed techniques, in terms of accuracy and computational time.

Keywords: multi-verse optimizer; weighted least square; harmonics estimation; power quality; artificial intelligence (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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