Fotovoltaik Model Parametrelerinin Optimal Tanımlanması için Tazmanya Canavarı Optimizasyonu

Abstract

Dünya genelinde, elektrik üretiminin kaynaklara göre dağılımı incelendiğinde, fotovoltaik (PV) sistemlerin elektrik üretiminde önemli bir paya sahip olduğu görülmektedir. Bu durum göz önüne alındığında, PV sistem verimliliğini artırmak için PV hücresinin akım-gerilim ölçüm verilerine dayalı yüksek doğruluklu modeller geliştirilmelidir. Literatürde, PV hücre modelleri olarak genellikle tek diyotlu ve iki diyotlu devreler kullanılmaktadır. Modellerin hassasiyeti, çoğunlukla karakteristik parametrelerin doğruluğuna bağlıdır. Bu parametrelerin, PV hücresi ölçüm verileri kullanılarak etkili ve doğru bir şekilde tahmin edilmesi gerekmektedir. Tahmini ve deneysel ölçüm verileri arasındaki en iyi uyumu sağlayan optimal parametreleri elde etmek için en çok tercih edilen optimizasyon yöntemleri meta-sezgisel algoritmalardır. Bu çalışma, optimal PV model parametrelerini belirlemek için Tazmanya canavarı optimizasyon (TDO) algoritmasını önermektedir. Önerilen yöntem, literatürde yaygın olarak kullanılan güneş hücrelerine uygulanmıştır. Önerilen yöntemin performansı, literatürdeki diğer yöntemlerle karşılaştırılarak değerlendirilmiştir. Tek diyotlu ve iki diyotlu devreler ile PV modülü için TDO kullanılarak elde edilen PV hücre modellerinin, diğer yöntemlerle elde edilen modellere kıyasla deneysel verilerle daha yüksek doğrulukta eşleşme sağladığı görülmüştür.

Keywords

• Fotovoltaik hücreler
• Parametre tahmini
• Metasezgisel algoritmalar
• Tazmanya canavarı optimizasyonu
• Optimizasyon

Tasmanian devil optimization for optimal identification of photovoltaic model parameters

Abstract

In the whole world, when the distribution of electricity generation according to resources is examined, it is seen that photovoltaic (PV) systems constitute an important part of electricity generation. Considering this situation, to improve the PV system efficiency, high-accuracy models for PV cells should be developed depending on the current-voltage measurement data of the PV cell. In literature studies, single-diode and two-diode circuits are often utilized as PV cell models. The precision of the models is frequently determined by the accuracy of the characteristic parameters. These parameters need to be estimated effectively and accurately using PV cell measurement data. To get the optimal parameters that provide the best match between the estimated and experimental measurement data, metaheuristics are the most preferred optimization methods. This study proposed the Tasmanian devil optimization (TDO) algorithm for identifying the optimal PV model parameters. The proposed method is applied to solar cells that are frequently used in literature. The performance of the proposed method is evaluated by comparing it with other literature methods. It is seen that the PV cell models obtained by using TDO for two diode circuits, i.e. single-diode and two-diode, and PV module, demonstrate higher accuracy in matching experimental data compared to other models obtained by different methods.

Keywords

• Photovoltaic cells
• Parameter estimation
• Metaheuristic algorithms
• Tasmanian devil optimization
• Optimization

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