The Experimental Study of Dust Effect on Solar Panel Efficiency

Yıl 2022, , 1429 - 1434, 16.12.2022

Atıl Emre Coşgun , Hasan Demir

https://doi.org/10.2339/politeknik.903989

Cited By: 10

Öz

This study shows the dust effect on solar panel efficiency based on experimental measurements. Sieve analysis has been performed to investigate the effect on the efficiency of the panel. Dust particles have been divided into different sizes such as (-75), (+75/-105), (+105/-250), (+250/-450). In addition, each piece weighed 20 g, uniformly sprinkled onto a 40-Watt SUNNY polycrystalline panel. In order to obtain the output voltages of the PV panel used a data acquisition card. Additionally, a photodiode sensor has been used in order to obtain the light reflection data from the panel to the outside while there had covered different diameters of dust particles on the panel. The data set consisting of electrical parameters have been used to compered both experimental study and Artificial Neural Network (ANN) output. There were 5 different data sets with the clean PV panel in this study (randomly selected data from it used as %40 training - %60 test) and the clean panel data have been used twice in the training and test part of the ANN. In this study, it has been observed that the ANN method can be used to estimate panel efficiency due to the linearity (The R-value was gotten nearly equal to 1 and it shows that there is a linear relationship between outputs and targets.) if the appropriate transfer function is selected. Also, this study shows that as the particle diameter covering the panel gets smaller, the output voltage of the panel decreases linearly.

Anahtar Kelimeler

Artificial neural network, dust, pv, sieve

Tozlanmanın solar panel verimlilikleri üzerine deneysel çalışma

Öz

Bu çalışma, deneysel ölçümlere dayalı olarak güneş paneli verimliliği üzerindeki toz etkisini göstermektedir. Panelin verimine etkisini araştırmak için elek analizi gerçekleştirilmiştir. Toz partikülleri (-75), (+75/-105), (+1105/-250), (+250/-450) gibi farklı boyutlara ayrılmış ve her bir toz parçacıkları 20 g olarak ayarlanmıştır. Toz parçacıkları, 40-Watt'lık bir SUNNY polikristal panel üzerine homojen bir şekilde dağıtılmıştır. PV panelinin çıkış voltajını elde etmek için veri toplama kartı kullanılmıştır. Ayrıca panel üzerinde farklı çaplarda toz parçacıkları kaplanmışken, panel yüzeyinden yansıyan ışıkların toplanması için fotodiyot sensör kullanılmıştır. Elektriksel parametrelerden oluşan veri seti hem deneysel çalışma hem de Yapay Sinir Ağı (YSA) çıktısının karşılaştırılması için kullanılmıştır. Bu çalışmada temiz PV panel ile 5 farklı veri setinden yararlanılmış (veriler rastgele % 40 eğitim -% 60 test olarak kullanılmıştır) ve temiz panel verileri YSA'nın eğitim ve test kısmında iki kez kullanılmıştır. Ayrıca çalışmamızda YSA metodu kullanılarak, uygun transfer fonksiyonu seçildiği takdirde panel verimliliğini tahmin edilebilecceği gözlemlenmiştir (veriler doğrusal olmasından dolayı R değeri 1'e yakın çıkmış, çıktılar ile hedefler arasında doğrusal bir ilişki olduğunu görülmüştür). Ayrıca bu çalışmada, paneli kaplayan toz parçacıklarının çapı küçüldükçe, panelin çıkış voltajının doğrusal olarak azaldığını görülmektedir.

Anahtar Kelimeler

Güneş enerjili hava kollektörü, konik yay, bulanık mantık, modelleme, çıkış sıcaklığı, termal verim

Kaynakça

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