Akademik Veri Yönetim Sistemi
Gumushane Universitesi Fen Bilimleri Dergisi, cilt.15, sa.2, ss.620-638, 2025 (Scopus)
The increasing competition in the energy sector and the growing demand of users for higher quality energy have made power quality a priority issue in electrical networks. One of the parameters affecting power quality is harmonics. In power systems, harmonics can lead to various undesirable situations such as distortion of voltage and current waveforms, excessive current and voltage rise due to resonance phenomena, inaccurate measurements in meters, insulation failures, malfunctions in electronic devices, additional energy losses, and overheating. Therefore, harmonics have become a frequently studied research area in recent years. In this study, hybrid methods combining recently developed algorithms such as African Vulture Optimization Algorithm (AVOA), Artificial Rabbit Optimization (ARO), Spider Wasp Optimization (SWO), Mountain Gazelle Optimization (MGO), and Aquila Optimization (AO) with the Least Squares (LS) method were employed for harmonic detection, and their results were analyzed. In the analyses, a commonly used test signal from the literature was examined. The harmonic amplitudes of this signal were determined using the Least Squares (LS) method, while the phase angles were estimated using hybrid methods (e.g., MGO-LS) incorporating the relevant metaheuristic algorithms. The results obtained showed that among the five examined methods, the proposed MGO-LS provided more accurate and reliable estimations even under noiseless and Gaussian noisy conditions. This indicates that the MGO-LS algorithm is an effective method for harmonic detection for the problem under investigation.