Performance of the Rapid Convergence Time for The Perturb and Observe MPPT Algorithm by Using Harris Hawks Optimization in Photovoltaic Systems

Öz

The efficiency of Maximum Power Point Tracking (MPPT) algorithms is crucial for optimizing the performance of photovoltaic (PV) systems. Traditional methods like the Perturb and Observe (P&O) algorithm are commonly used due to their simplicity, but they often suffer from issues such as slow convergence and oscillations around the maximum power point under changing environmental conditions. This study introduces an enhanced P&O algorithm by integrating it with Harris Hawks Optimization (HHO), a nature-inspired optimization technique known for its robust convergence characteristics. The proposed hybrid P&O-HHO algorithm aims to accelerate convergence time and improve the overall tracking performance of the PV system. To maximize power from PV modules at varying sun irradiance levels, Harris-Hawks Optimization (HHO) is offered as a performance improvement method for the conventional Perturb and Observe (P&O) approach in photovoltaic systems. The proposed model encompasses a boost converter for DC-DC power controlled by an MPPT algorithm, a PV panel, and a resistive load. The MPPT algorithm proposed is founded upon the execution of a hybrid technique that combines Harris-Hawks Optimization, a new method inspired by nature, and the conventional P&O approach. The suggested method has been tested through simulation testing utilizing the environment created by MATLAB Simulink. The findings of the simulation illustrate that‎‎ the HHO-P&O MPPT algorithm, as described, successfully ‎identified the global maximum power point more ‎efficiently.‎ Additionally, it exhibited a rapid convergence speed, superior outcomes in comparison to the standard Perturb and Observe method, and a swift dynamic reaction.

Anahtar Kelimeler

• Maximum Power Point Tracking
• ‎ Harris-Hawks Optimization
• Perturb and Observe‎
• Photovoltaic

Fotovoltaik Sistemlerde Harris Hawks Optimizasyonu Kullanılarak Gözlem ve Bozma MPPT Algoritması İçin Hızlı Yakınsama Süresinin Performansı

Öz

Maksimum Güç Noktası İzleme (MPPT) algoritmalarının verimliliği, fotovoltaik (PV) sistemlerin performansını optimize etmek için çok önemlidir. Perturb ve Observe (P&O) algoritması gibi geleneksel yöntemler, basitlikleri nedeniyle yaygın olarak kullanılır, ancak genellikle yavaş yakınsama ve değişen çevre koşulları altında maksimum güç noktası etrafında salınımlar gibi sorunlardan muzdariptirler. Bu çalışma, sağlam yakınsama özellikleriyle bilinen doğadan ilham alan bir optimizasyon tekniği olan Harris Hawks Optimizasyonu (HHO) ile entegre edilerek geliştirilmiş bir P&O algoritması sunmaktadır. Önerilen hibrit P&O-HHO algoritması, yakınsama süresini hızlandırmayı ve PV sisteminin genel izleme performansını iyileştirmeyi amaçlamaktadır. Değişen güneş ışınımı seviyelerinde PV modüllerinden gelen gücü en üst düzeye çıkarmak için, fotovoltaik sistemlerde geleneksel Perturb and Observe (P&O) yaklaşımı için bir performans iyileştirme yöntemi olarak Harris-Hawks Optimizasyonu (HHO) önerilmektedir. Önerilen model, bir MPPT algoritması, bir PV paneli ve bir dirençli yük tarafından kontrol edilen DC-DC gücü için bir yükseltme dönüştürücüsünü kapsar. Önerilen MPPT algoritması, doğadan ilham alan yeni bir yöntem olan Harris-Hawks Optimizasyonu ile geleneksel P&O yaklaşımını birleştiren hibrit bir tekniğin uygulanması üzerine kurulmuştur. Önerilen yöntem, MATLAB Simulink tarafından oluşturulan ortamdan yararlanılarak simülasyon testi yoluyla test edilmiştir. Simülasyonun bulguları, HHO-P&O MPPT algoritmasının, açıklandığı gibi, küresel maksimum güç noktasını daha verimli bir şekilde başarılı bir şekilde tanımladığını göstermektedir. Ek olarak, standart Perturb ile karşılaştırıldığında hızlı bir yakınsama hızı, üstün sonuçlar sergiledi ve Yöntemi ve hızlı dinamik reaksiyonu gözlemleyin.

Anahtar Kelimeler

• Maksimum Güç Noktası Takibi
• Harris-Hawks Optimizasyonu
• Perturb and Observe
• Fotovoltaik

Kaynakça

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