Genetik Algoritma ile Optimize Edilen Bulanık Mantık Denetleyici kullanan Güneş Takip Sistemi Tasarımı ve Uygulaması

Bu çalışma, değişen güneş pozisyonlarına göre fotovoltaik panelden maksimum performansı sağlayan güneş takip sistemi için zeki bir kontrol algoritması tanımlar. Güneş Takip Sistemi, fotovoltaik panellerin etkinliğini yükseltmek için çift eksen olarak tasarlandı. Güneş Takip Sisteminde Azimut ve Zenit açılarını kontrol etmek ve maliyetleri minimize etmek için DC motorlar tercih edildi. Güneşin pozisyonunu yüksek doğrulukla izlemek için bu motorların hız kontrollerinde Bulanık Mantık Algoritmaları kullanıldı. Motorları kontrol etmek üzere Bulanık Mantık Denetleyicisinin tasarlanmasından sonra denetleyicinin üyelik fonksiyonları ve kontrol kuralları, doğal seçim ve genetik mekaniği temel alan bir optimizasyon algoritması olan Genetik Algoritmalar tarafından bulunur. Bu çalışmada sonuç olarak, sabit sistem üzerine pozisyonlanmış fotovoltaik panel ile geliştirilen güneş takip sistemi üzerine pozisyonlanmış fotovoltaik panel arasında güç performansı karşılaştırıldı. Karşılaştırma sonuçlarına göre güneş takip sistemi üzerine pozisyonlanan panel mevsimlere bağlı olarak değişen oranlarda daha yüksek performans gösterdiği gözlemlendi.

DESIGN AND APPLICATION OF SOLAR TRACKING SYSTEM USING OPTIMIZED FUZZY LOGIC CONTROLLER BY GENETIC ALGORITHM

This study describes an intelligent control algorithm for the solar tracking system (STS) providing maximum performance from the photovoltaic panel according to different sun positions. The solar tracking system is designed as dual axis to increase the efficiency of photovoltaic panels. DC motors are preferred in order to minimize cost and to control the azimuth and zenith angles in the solar tracking system. Fuzzy logic algorithms are used to adjust the speed of these motors to track the sun’s position with a high degree of accuracy. After designing a fuzzy logic controller in order to control the motors, membership functions of controller and control rules are simultaneously found by genetic algorithms which is an optimization algorithm based on natural selection and genetic mechanics. As a result in the study, the power performance analysis is compared between a photovoltaic panel positioned on the designed solar tracking system and a photovoltaic panel positioned on the static system. According to comparison results, the photovoltaic panel positioned on the solar tracking system is observed that it shows higher performance at varying rates of depending on the seasons.

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