Energy-exergy modeling of solar radiation with most influencing input parameters. Issue 17 (2nd September 2019)

• Record Type: Journal Article
• Authors: Taki, Morteza; Rohani, Abbas; Yildizhan, Hasan; Farhadi, Rouhollah
• Is Part Of: Energy sources. Volume 41:Issue 17(2019)
• Page Start: 2128
• Page End: 2144
• Publication Date: 2019-09-02
• Subjects: Solar radiation exergy -- Hakkari province of Turkey -- Gaussian process regression (GPR) -- solar energy -- modeling; Natural resources -- Periodicals; Energy consumption -- Periodicals; Energy consumption -- Climatic factors -- Periodicals; Energy conversion -- Periodicals; Energy conversion -- Environment aspects -- Periodicals; Power (Mechanics) -- Periodicals; 333.7905
• DOI: 10.1080/15567036.2018.1550126
• Languages: English
• ISSNs: 1556-7036

Abstract

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 ( Tave, Tmax, Tmin ), 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 ( R 2 ) 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.