new empirical models for estimation of diffuse radiation using satellite data

Diffuse radiation is used in photovoltaic systems and other energy applications. since global radiation is measured by local meteorological stations, it is possible to reach these radiation data. however, diffuse radiation is not usually measured, so it is not possible to obtain regular data on diffuse radiation. for this reason, efforts are underway to develop various empirical models to estimate diffuse radiation. this paper aims to develop new empirical models to estimate the diffuse radiation values for konya, türkiye. the empirical models are used to determine the relationship between the diffuse fraction and the clearness index. data from nasa-surface meteorology and solar energy and the measured global solar were used. the three most suitable developed models were selected, and it was suggested to estimate the diffuse radiation. the developed models consist of 2nd, 3rd, and 4th-order polynomial regression models. the proposed models were tested to evaluate their performances by using eight statistical methods. these are mean bias error (mbe), mean absolute error (mae), mean squared error (mse), root mean squared error (rmse), sum squared relative error (ssre), relative standard error (rse), coefficient of determination (r2) and correlation coefficient (r). for the suggested models, the statistical parameters r2 value were calculated as 0.999705413, 1, and 1, and the rse values were determined as 0.0084537, 0.000122, and 6.05e-06. the proposed models can contribute to researchers working on the applications of photovoltaic systems. the approaches could be used to estimate diffuse radiation elsewhere under similar climatic conditions.