Estimation of solar radiation using artificial neural networks with different input parameters for Mediterranean region of Anatolia in Turkey

An artificial neural network (ANN) model was used to estimate the solar radiation parameters for seven cities from Mediterranean region of Anatolia in Turkey. As well known that Turkey is a bridge between Asia and Europe and it lies in a sunny belt, between 36° and 42°N latitudes. Indeed, the country has sufficient solar radiation intensities for solar applications. In order to make estimation of solar radiation, the data from the Turkish State and Meteorological Service were used. Data of 2006 were used for testing and data of 2005, 2007, and 2008 were estimated. Effects of number of input parameters were tested on solar radiation that was output layer. With this aim, number of input layer parameters changed from 2 to 6. The obtained results indicated that the method could be used by researchers or scientists to design high efficiency solar devices. It was also found that number of input parameters was the most effective parameter on estimation of future data on solar radiation.

Research highlights
► An artificial neural network (ANN) model was used in this work.
► The main originality of the study was the testing of input parameters on results and R2 values.
► The input parameters were the most effective parameters on estimation of future data on solar radiation.