Method and strategy for predicting daily global solar radiation using one and two input variables for Indian stations

Abstract

Estimation of daily global solar radiation (GSR) for a particular location is a key parameter in modeling and designing any solar energy system. Very limited observatory stations are available to collect solar radiation data. This demands solar radiation estimation for new locations where there is no observatory station. In the present study, solar radiation models are developed for estimating daily GSR for sunny locations of India. Solar radiation data are collected for a period of three years from in situ measurements. Angstrom-Prescott linear correlation and nonlinear correlations such as quadratic, cubic, exponential, and power models are developed based on the bright sunshine duration. In this new approach, the “bright sunshine duration” is estimated by a new variable named “approximate bright sunshine duration.” The developed linear one input parameter model is applied to predict the daily GSR for five other Indian locations, namely, Allahabad, Bhopal, Chennai, Hyderabad, and Mumbai. The developed linear one input parameter model was further modified as a latitude dependent model to improve the accuracy of the model and named as the latitude model. The performance of all the models is analysed by using the statistical tools, namely, Relative Root Mean Square Error, Mean Percentage Error, and Mean Absolute Percentage Error. The latitude model resulted in fair to good estimations for Tiruchirappalli and the other five Indian locations of latitudes ranging from 10°N to 26°N. Further, other solar radiation models from the literature were considered to identify their applicability for the same selected locations. The models recommended for the selected Indian locations are presented. Out of all the universal models, the monthly mean daily GSR model of Page and out of all Indian models, the monthly mean daily GSR models of Katiyar and Mani showed satisfactory performance for the majority of selected Indian locations.