AI Summary & Key Takeaways
AI InsightIt is expected that the new model will be beneficial to everyone who is the solar engineers, architects, agriculturists, and hydrologists involved or interested in the design and study of solar energy applications such as solar furnaces, wood drying, stoves, concentrating collectors, interior illumination and thermal load analyzing of buildings, and photovoltaics, agricultural and meteorological forecasting.
📌 3 Key Takeaways
Abstract
Solar radiation data are required for many applications and many areas of research. In order to achieve this, several empirical models have been suggested to predict the global solar radiation in Turkey and other countries. The different meteorological data as the global solar radiation, the sunshine duration, the temperature, the atmospheric pressure, the wind speed and the relative humidity were measured by Eskisehir Osmangazi University during the period between 01 January 2011 and 31 December 2014. These data were used to develop the empirical models in order to estimate the monthly average daily global solar radiation on the horizontal surface over Eskisehir City of Turkey. The developed empirical models were analyzed with the widely used nine statistical methods, namely; the relative percentage error (E), the mean percentage error (MPE), the mean absolute percentage error (MAPE), the sum of squares of relative errors (SSRE), the relative standard error (RSE), the mean bias error (MBE), the root mean square error (RMSE), the t-statistic method (t-stat) and coefficient of determination (R2). It is expected that the new model will be beneficial to everyone who is the solar engineers, architects, agriculturists, and hydrologists involved or interested in the design and study of solar energy applications such as solar furnaces, wood drying, stoves, concentrating collectors, interior illumination and thermal load analyzing of buildings, and photovoltaics, agricultural and meteorological forecasting.