Energy-exergy modeling of solar radiation with most influencing input parameters

ABSTRACT

In this study, a new soft computing model Gaussian process regression (GPR) was evaluated for modeling the total solar radiation (TSR) and exergy (Ф) in Hakkari province (the region with the highest sunshine duration), Turkey. For this purpose, meteorological data include average, maximum and minimum temperature (T_ave, T_max, T_min), relative humidity (H), sea level pressure (P), wind speed (W), and total sunbathing time (TST), wihch were used, and sensitivity analysis was applied for evaluating the results of TSR and Ф modeling. The results showed that all the input variables have significant impact on TSR and Ф modeling. Mean absolute percentage error and coefficient of determination (R²) for TSR and Ф predicted by GPR were 1.51–7.02% and 0.97–0.95, respectively. Application of five-fold cross validation method showed that GPR model is able to predict the TSR and Ф with a small size of data, but for more accuracy, it is suggested to use more than 70% of total data set for training the models. This research showed that GPR has a good ability for modeling the TSR and Ф with high accuracy, and so the engineers can use this method for the TSR and Ф prediction without using the solar radiation or exergy-to-energy ratio.

KEYWORDS:

• Solar radiation exergy
• Hakkari province of Turkey
• Gaussian process regression (GPR)
• solar energy
• modeling

Nomenclature

Ƞ_e Energy efficiency

Ƞ_e,max Maximum Energy efficiency

E_sr Energy of radiation (MJ m⁻²)

Φ Exergy of radiation (MJ m⁻²)

W_max Maximum work

I Incidence of solar radiation (MJ m⁻²)

T Temperature (K)

ANFIS Adaptive Network Based Fuzzy Inference System

SVM Support Vector Machine

GPR Gaussian Process Regression

T_sr Solar radiation temperature (6000 K)

Ѱ Exergy-energy ratio of solar radiation

H Daily average relative humidity (%)

T_max Daily maximum temperature (^°C)

T_min Daily minimum temperature (^°C)

T_ave Daily average temperature (^°C)

TST Total Sunbathing Time

WS Wind Speed (ms⁻¹)

P Pressure (mbar)

MAPE Mean Absolute Percentage Error

TSR Total Solar Radiation

T₀ Ambient temperature (K)

Acknowledgments

The authors would like to thank the editor in chief and the anonymous referees for their valuable suggestions and useful comments that improved the paper content substantially. This study was supported by Agricultural Sciences and Natural Resources University of Khuzestan, Iran. The authors are grateful for the support provided by this university.