Study of Global Solar Radiation Estimation based on Artificial Neural Networks Techniques

Abstract

Abstract Solar Radiation data received by earth in the form of x-rays, UV-rays, infrared rays is a prominent and useful data as it gives the information about the amount of energy received from sun at the earth. Artificial Neural Network (ANN) is brain inspired technology which learns and performs in a way similar to the way our human brain performs. Sun’s energy is of utmost importance and is freely available in uncountable amount so it has amazing future in energy world. As the energy demands are increasing rapidly day by day with the advent of technology, it raises the need of estimation and prediction of this renewable and sustainable energy source. This estimation leads to better utilization as well as limits the over consumption. This paper deals with estimation of global solar radiation and its importance and the related conventional and non-conventional methodology and approaches. The possible approaches can be AI based techniques such as ANN, fuzzy logic, expert system etc. or it can be done with the help of empirical modeling and various other modeling techniques on the basis of radiation data available in huge amount, for estimation as well as forecasting. Keywords: Global Solar Radiation, ANN, empirical modeling, fuzzy logic, radiation estimation. Cite this Article Deepa Rani Yadav, Deependra Pandey, Stuti Shukla Datta. Study of Global Solar Radiation Estimation based on Artificial Neural Networks Techniques. Recent Trends in Electronics & Communication Systems . 2020; 7(1): 26–31p.