Open AccessChoice of ideal sunshine hour based model to predict global solar radiation in India
Author(s) -
Suman Samanta,
Saon Banerjee,
Patra Pulak Kumar,
Maiti Sudhansu Sekhar,
N. Chattopadhyay
Publication year - 2021
Publication title -
mausam
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.243
H-Index - 12
ISSN - 0252-9416
DOI - 10.54302/mausam.v71i3.46
Subject(s) - sunshine duration , mean squared error , statistics , empirical modelling , solar energy , linear regression , regression analysis , mathematics , meteorology , logarithm , exponential function , environmental science , geography , computer science , simulation , precipitation , ecology , mathematical analysis , biology
Solar radiation is the key energy source for most of the energy conversion systems, whether it is biological or mechanical. It is also the most fundamental energy source for future energy demand. Like most of the developing countries, India also lacks sufficient instrument facilities to measure global solar radiation (GSR) at recommended spatial interval and alternative approaches must be used to generate GSR data. In the present study, six well known empirical models were tested to estimate the GSR over twelve major cities of India using long-term global solar radiation and bright sunshine hour data. The empirical coefficients have been calculated for all the models and each location using regression analysis method. Daily GSR are then calculated using those regression constants along with statistical analysis. Results reveal that all the models shows close estimation with low mean bias error (MBE), root mean square error (RMSE) and mean percentage error (MPE) values. Among all models, linear exponential and linear logarithmic models are highly recommended for prediction of GSR throughout the country, except Shillong, where Bakircilinear exponential model is recommended. Significance tests i.e., t-test also confirms that this two model produce most significant results than others.