Comparison of advanced metaheuristic algorithms for harmonic detection in power systems

Yıl 2025, Cilt: 15 Sayı: 2, 620 - 638, 15.06.2025

Şule Nilhan Oğuzalp , Sıtkı Akkaya , Ulaş Eminoğlu

https://doi.org/10.17714/gumusfenbil.1618127

Öz

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.

Anahtar Kelimeler

Mountain gazelle optimization , Least square method , Power quality , Harmonic

Güç sistemlerinde harmonik tespiti için gelişmiş meta sezgisel algoritmaların karşılaştırılması

Öz

Enerji sektöründe rekabetin artması ve kullanıcıların daha kaliteli enerji talep etmesi, elektrik şebekelerinde güç kalitesini öncelikli bir konu haline getirmiştir. Güç kalitesini etkileyen parametrelerden biri de harmoniklerdir. Harmonikler güç sistemlerinde; gerilim-akım dalga şekillerinin bozulması, rezonans olayları sonucunda aşırı akım ve gerilim yükselmesi, sayaçlarda yanlış ölçmeler, yalıtım hataları ve elektronik cihazların arızalanmasına, ek enerji kayıpları ve ısınmalar gibi birçok istenmeyen durumlara neden olabilir. Bu nedenle harmonikler son yıllarda üzerinde sıkça çalışılan bir araştırma alanı olmuştur. Bu çalışmada, son yıllarda geliştirilen AVOA (African Vulture Optimization Algorithm), ARO (Artificial Rabbit Optimization), SWO (Spider Wasp Optimization), MGO (Mountain Gazelle Optimization) ve AO (Aquila Optimization) algoritmaları ve En Küçük Kareler (Least Squares) yönteminin bir arada kullanıldığı hibrit yöntemler, harmoniklerin tespitinde kullanılarak sonuçları incelenmiştir. Analizlerde, literatürde sıkça kullanılan bir test sinyali üzerinde çalışılmıştır. Bu sinyalin harmonik genlikleri, En Küçük Kareler (Least Squares) yöntemiyle belirlenmiş, faz açıları ise ilgili meta sezgisel algoritmalar kullanılarak hibritleştirilmiş yöntemlerle (MGO-LS gibi) tahmin edilmiştir. Elde edilen sonuçlar, incelenen beş yöntem arasında önerilen MGO-LS’nın tahminleri gürültüsüz ve Gaussian gürültülü koşullarda bile daha doğru ve güvenilir olduğunu göstermiştir. Bu durum, incelenen problem için MGO-LS algoritmasının harmonik tespiti için etkili bir yöntem olduğunu ortaya koymaktadır.

Anahtar Kelimeler

Dağ ceylanı optimizasyonu , En küçük kareler yöntemi , Güç kalitesi , Harmonik

Etik Beyan

Bu makalenin yazarları, bu çalışmada kullanılan materyal ve yöntemlerin etik kurul izni ve / veya yasal-özel izin gerektirmediğini beyan etmektedir.

Teşekkür

Yazarlar, meta sezgisel optimizasyon yöntemleri konusunda değerli bilgilerini paylaşan Sivas Cumhuriyet Üniversitesi Teknoloji Fakültesi Öğretim Üyesi Doç. Dr. Sibel ARSLAN’a ve makalenin inceleme ve değerlendirme aşamasında yapmış oldukları katkılarından dolayı editör ve hakem/hakemlere teşekkür eder.

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