Prediction of solar radiation intensity in Yazd station by using regression model based on principal components (PCR)

Solar radiation reaching the earth's surface is one of the most important variables used in solar energy projects, hydrological modeling, evaporation and transpiration, meteorology and agriculture. In this research, the functionality of principal component analysis and linear multivariate regression was investigated in predicting the amount of solar radiation in Yazd station between 2010 to 2014 and 2015 to 2021. Variables of average temperature, minimum temperature, maximum temperature, hours of sunshine, relative humidity and solar radiation are received from the Meteorological Organization on a daily basis and variables of extraterrestrial solar radiation, relative distance from the earth to the sun, solar inclination angle and maximum hours of sunshine are calculated with the existing relations and was chosen as input of Principal component analysis method. The correlation of these parameters with the amount of solar radiation shows the presence of a significant positive relationship at the level of 1% between the amount of solar radiation and extraterrestrial radiation, the ratio of sunny hours, the average temperature and the relative distance from the earth to the sun, and with the solar inclination angle at the level of 5% and was observed a significant negative correlation at the level of 1% with relative humidity values. The results of the analysis of the main components showed that the first two components can be selected as the main components according to the eigenvalues of the parameters and the percentage of variance. The correlation coefficient of the first and second components with solar radiation was 0.893 and -0.168, respectively, and as a result, the first component has a higher correlation with the amount of solar radiation than the second component. The rotated value of loading in the first component shows that the minimum temperature, maximum temperature, average temperature and relative humidity are more correlated with solar radiation and the correlation of other factors (extraterrestrial radiation, solar inclination angle and relative distance from the earth to the sun and the ratio of sunny hours) is low in this component. Investigating the relationship between solar radiation and the values of the main components obtained from PC1 and PC2 using multivariate linear regression showed that the effect of meteorological parameters on solar radiation is significant (p < 0.001) and its R2 is was determined as 0.89%. The evaluation criteria of PCR and MLR methods show the ability of PCA method to estimate solar radiation.