An Improved Empirical Model for Estimation of Temperature Effect on Performance of Photovoltaic Modules

It is prerequisite to predict the behaviour of photovoltaic (PV) modules in a particular geographical area where the system is to be installed for their better performance and increasing lifetime. For that, models are the easiest and acceptable tools to characterise the behaviour of PV modules in an...

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Bibliographic Details
Published in:International journal of photoenergy 2019, Vol.2019 (2019), p.1-16
Main Authors: Jatoi, Abdul Rehman, Jakhrani, Abdul Qayoom, Samo, Saleem Raza
Format: Article
Language:English
Subjects:
Confidence intervals
Empirical analysis
Engineering
Error analysis
Humidity
Least squares method
Modules
Neural networks
Photovoltaic cells
Polycrystals
Researchers
Solar cells
Solar energy
Summer
System effectiveness
Temperature effects
Thin films
Variables
Winter
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Summary:It is prerequisite to predict the behaviour of photovoltaic (PV) modules in a particular geographical area where the system is to be installed for their better performance and increasing lifetime. For that, models are the easiest and acceptable tools to characterise the behaviour of PV modules in any location. The purpose of this study was to develop an empirical model to predict the influence of temperature on the performance of four different PV module technologies, namely, polycrystalline, monocrystalline, amorphous, and thin film in an outdoor environment. The model has been developed by fitting of one year experimental data using the least squares method. The estimated results of the developed model were validated with real-time data (winter and summer season) and a comparison of other existing model estimates using error analysis with 95% confidence interval. The proposed model estimations confirm that the monocrystalline module performs better in winter and polycrystalline in summer as compared to amorphous and thin film in the study area. During analysis, it is revealed that developed model results are more precise and appropriate among other existing model estimations. It is concluded that the proposed model estimations could be used for the prediction of PV module temperature in similar environmental conditions as that of the study area with more accuracy and confidence. It ultimately helps to develop cost-effective and efficient PV systems.
ISSN:1110-662X
1687-529X
DOI:10.1155/2019/1681353