GÜÇ SİSTEMİ HARMONİKLERİNİN ADAPTİF KESTİRİMİ: EĞİM DÜŞÜM TABANLI ADAPTİF ALGORİTMALARIN BAŞARIM ANALİZİ

Bu çalışmada, güç sistemi harmoniklerinin adaptif kestirimi üzerine bir inceleme yapılmıştır. Çalışmada adaptif kestirim algoritmaları olarak, basit hesap yükü ve gerçek zamanlı sistemlere kolaylıkla uygulanabilirliği nedeniyle literatürde yaygın kullanılan eğim düşüm tabanlı adaptif algoritmalar kullanılmıştır. Bu algoritmalar sırasıyla en küçük ortalama kare (LMS), normalize edilmiş LMS (NLMS), İşaret-Veri LMS ve İşaret-Hata LMS algoritmalarıdır. Çalışma kapsamında, öncelikle güç sistemlerinde mevcut olan akım veya gerilim ifadelerinin bilinmeyen genlik ve faz harmonikleri bir kestirim problemi olarak ifade edilmiştir. Daha sonra ise ele alınan güç sistemi sinyalinin temel ve harmonik bileşenlerin genlik ve faz bilgileri eğim düşüm tabanlı adaptif algoritmalar ile kestirilmiştir. Çalışmada gerçekleştirilen benzetimler, NLMS algoritmasının diğer üç algoritmaya kıyasla üstün bir başarım sergilediğini göstermiştir. Fakat yüksek hızlı veri akışının mevcut olduğu gerçek zamanlı güç sistemi uygulamalarında LMS ve NLMS algoritmalarının yerine, daha az hesap yükü içeren İşaret-Veri LMS algoritmasının kullanımının daha uygun olabileceği sonucuna ayrıca varılmıştır.

Anahtar Kelimeler:

Eğim düşüm algoritmaları, Adaptif kestirim, Güç sistemi harmonikleri

ADAPTIVE ESTIMATION OF POWER SYSTEM HARMONICS: PERFORMANCE ANALYSIS OF GRADIENT DESCENT-BASED ADAPTIVE ALGORITHMS

In this study, adaptive estimation of power system harmonics is investigated. As adaptive estimation algorithms in the study, gradient descent based adaptive algorithms widely used in the literature are used due to its simple computational complexity and the easily applicable for real-time systems. These algorithms are least mean square LMS, normalized LMS (NLMS), Sign-Data LMS, and Sign-Error LMS algorithms, respectively. Within the scope of the study, the unknown amplitude and phase harmonics of the current or voltage expressions available in power systems are first expressed as an estimation problem. Then, the handled amplitude and phase information of the fundamental and harmonic components of the power system signal are estimated by the gradient descent based adaptive algorithms. The simulations performed in the study indicate that the NLMS algorithm shows superior performance compared to the other three algorithms. However, in real-time power system applications where the high-speed data stream is available, it is also concluded that the use of the Sign-Data LMS algorithm containing lower computational complexity will be more appropriate instead of the LMS and NLMS algorithms.

Keywords:

Gradient descent algorithms, Adaptive estimation, Power system harmonics,

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