Fotovoltaik Hücre Parametrelerinin Hassas Tahmini için Yeni Bir Hibrit Savaş Stratejisi Algoritması–Diferansiyel Evrim–Ardışık En Küçük Kareler Kuadratik Programlama (WSA-DE-SLSQP) Yöntemi

Öz

PV sistemlerin güvenilir tasarımı, performans değerlendirmesi ve maksimum güç noktası izleme (MPPT) gibi uygulamaların sağlıklı yürütülebilmesi için panellerin akım-gerilim (I–V) karakteristiklerinin doğru bir şekilde modellenmesi ve belirlenmesi gerekmektedir Bu çalışma, fotovoltaik (PV) hücre ve panellerin akım–gerilim (I–V) karakteristiklerinin doğru modellenmesi ve parametrelerinin yüksek doğrulukla tahmin edilmesine yönelik yeni bir hibrit yaklaşım sunulmuştur. Analizlerlerde, tek diyot (SDM) ve çift diyot (DDM) eşdeğer devre modelleri kullanılarak PV parametre kestirimi ele alınmıştır. Çalışmada, PV panelin I–V eğrileri kapasitif yük temelli deneysel bir ölçüm sistemi ile elde edilmiştir. Doğrusal olmayan ve çok parametreli bu problem için klasik deterministik yöntemlerin sınırlamalarını aşmak amacıyla yeni bir hibrit meta-sezgisel optimizasyon algoritması olan WSA-DE-SLSQP önerilmiştir. Bu yöntem; küresel arama için Savaş Stratejisi Algoritması (WSA), mikro ölçekli iyileştirme için Diferansiyel Evrim (DE) ve fiziksel kısıtlar altında hassas yerel optimizasyon için Ardışık En Küçük Kareler Kuadratik Programlama (SLSQP) aşamalarından oluşmaktadır. Önerilen yaklaşım, Cheetah Optimizer (CO), Crayfish Optimization Algorithm (CFOA) ve Mountain Gazelle Optimizer (MGO) ile karşılaştırılmıştır. Sonuçlar, WSA-DE-SLSQP algoritmasının hem tek hem de çift diyot modellerinde en düşük hata değerlerini ve en yüksek uyum katsayılarını sağladığını göstermiştir. Elde edilen bulgular, önerilen hibrit yöntemin PV parametre tahmininde yüksek doğruluk ve güvenilirlik sunduğunu ortaya koymaktadır.

Anahtar Kelimeler

• PV karakteristik
• optimizasyon
• War strateji

A Novel Hybrid War Strategy Algorithm–Differential Evolution Sequential Least Squares Quadratic Programming (WSA-DE-SLSQP) for Accurate Parameter Estimation of Photovoltaic Cell

Abstract

For the reliable design of PV systems and the effective implementation of applications such as performance evaluation and maximum power point tracking (MPPT), it is essential to accurately model and determine the current–voltage (I–V) characteristics of photovoltaic panels. This study presents a novel hybrid approach aimed at accurately modeling the I–V characteristics of photovoltaic (PV) cells and panels and estimating their parameters with high precision. In the analyses, PV parameter extraction is performed using single-diode (SDM) and double-diode (DDM) equivalent circuit models. In this study, the I–V curves of the PV panel are obtained using a capacitive-load-based experimental measurement system. To overcome the limitations of classical deterministic methods in solving this nonlinear and multi-parameter problem, a new hybrid metaheuristic optimization algorithm, namely WSA-DE-SLSQP, is proposed. This method consists of the War Strategy Algorithm (WSA) for global exploration, Differential Evolution (DE) for micro-scale refinement, and Sequential Least Squares Quadratic Programming (SLSQP) for precise local optimization under physical constraints. The proposed approach is compared with the Cheetah Optimizer (CO), Crayfish Optimization Algorithm (CFOA), and Mountain Gazelle Optimizer (MGO). The results demonstrate that the WSA-DE-SLSQP algorithm achieves the lowest error values and the highest goodness-of-fit coefficients for both single- and double-diode models. The obtained findings confirm that the proposed hybrid method provides high accuracy and reliability in PV parameter estimation.

Keywords

• pv characteristic
• optimization
• war strategy

Kaynakça

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