Estimation of Solar Radiation Exergy by Artificial Neural Networks Using Meteorological and Geographical Data

Solar radiation is source of energy, which can generate power in two ways. Producing electric energy using photovoltaic panels or by means of a thermodynamic cycle. The amount of generated energy, which can do work by a system is changing daily, monthly, and seasonally depending on exergy, in both cases. Some models are proposed to study the exergy of incident solar radiation on the horizontal surface, which can be used to produce work. It is always important to know how much work can be obtained from solar radiation. In this study, the prediction of solar radiation exergy in Kerman province in south-east of Iran was developed. The main aim of this paper is to study the exergy of the south-east of Iran and find the best places in case of suitable solar radiation exergy. It will cause to the select the best places for investment in solar energy utilization. The results show that Anar, Zarand, and Sirjan are the best places of province in case of high solar radiation exergy values. Although Kahnuj, Bam, and Jiroft have the high solar radiation values, but the solar radiation exergy in these locations is less than the other cities. The results show that the total energy quality factor (the exergy-to-energy ratio) of extraterrestrial solar radiation by Petela expression is about 0.9328. The predicted mean annual solar radiation exergy values were given in form of map that were made by using ArcGIS.

کلیدواژه ها:

Solar radiation ، solar radiation exergy ، ArcGIS