TY - JOUR
T1 - Prediction of dust particle size effect on efficiency of photovoltaic modules with ANFIS
T2 - An experimental study in Aegean region, Turkey
AU - Adıgüzel, Ertuğrul
AU - Özer, Emre
AU - Akgündoğdu, Abdurrahim
AU - Ersoy Yılmaz, Aysel
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In this study, the effect of coal dust in variable sizes and weight on photovoltaic (PV) modules’ performance has been examined under laboratory conditions. Experimental studies have been performed under Standard Test Conditions (STC: Radiance: 1000 W/m2; Cell temperature: 25 °C; Sun Spectrum: AM 1.5) for monocrystalline silicon (m-Si) and polycrystalline silicon (p-Si) PV modules. By using sieve analysis, the particle sizes of coal dust have been divided into six groups which are in µm size and as follows: (−38), (+38/−53), (+53/−75), (+75/−106), (+106/−250), (+250/−500). Artificial pollution has been created by uniformly distributing coal dust of certain size and weight onto PV modules. Three different weights of coal dust (5 g, 10 g and 15 g) have been employed for every single size of coal dust. In order to investigate the effect of any particle size and any weight of coal, the performance of PV modules has been investigated by measuring voltage, current and power. The data set consisting of electrical parameters has been used to develop a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS). Comparison of experimental and ANFIS results have been given by calculating of Root Mean Square Error (RMSE) and coefficient of determination (R2). The performance indices have been calculated as RMSE = 0.18719 and R2 = 0.99803 for m-Si, RMSE = 0.87098 and R2 = 0.99714 for p-Si PV modules. According to the results, for a given particle size and weight, the ANFIS model is quite successful in power estimation for PV modules.
AB - In this study, the effect of coal dust in variable sizes and weight on photovoltaic (PV) modules’ performance has been examined under laboratory conditions. Experimental studies have been performed under Standard Test Conditions (STC: Radiance: 1000 W/m2; Cell temperature: 25 °C; Sun Spectrum: AM 1.5) for monocrystalline silicon (m-Si) and polycrystalline silicon (p-Si) PV modules. By using sieve analysis, the particle sizes of coal dust have been divided into six groups which are in µm size and as follows: (−38), (+38/−53), (+53/−75), (+75/−106), (+106/−250), (+250/−500). Artificial pollution has been created by uniformly distributing coal dust of certain size and weight onto PV modules. Three different weights of coal dust (5 g, 10 g and 15 g) have been employed for every single size of coal dust. In order to investigate the effect of any particle size and any weight of coal, the performance of PV modules has been investigated by measuring voltage, current and power. The data set consisting of electrical parameters has been used to develop a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS). Comparison of experimental and ANFIS results have been given by calculating of Root Mean Square Error (RMSE) and coefficient of determination (R2). The performance indices have been calculated as RMSE = 0.18719 and R2 = 0.99803 for m-Si, RMSE = 0.87098 and R2 = 0.99714 for p-Si PV modules. According to the results, for a given particle size and weight, the ANFIS model is quite successful in power estimation for PV modules.
KW - ANFIS
KW - Coal dust
KW - Particle size
KW - Photovoltaic modules
UR - http://www.scopus.com/inward/record.url?scp=85057880070&partnerID=8YFLogxK
U2 - 10.1016/j.solener.2018.12.012
DO - 10.1016/j.solener.2018.12.012
M3 - Article
AN - SCOPUS:85057880070
SN - 0038-092X
VL - 177
SP - 690
EP - 702
JO - Solar Energy
JF - Solar Energy
ER -
