A Review of Machine Learning Models Developed for Solar Radiation Forecasting for Indian Regions

These Ever after since the development in technology, many applications are evolved which are based on solar energy utilization and importance of Global solar radiation (GSR) information is consistently increasing. However, due to the changes in solar-radiation and lac of measurement infrastructure, availability of accurate information on GSR data is poor. To deal with this employment of AI based solution is considered. Many machine learning models are developed for forecasting the GSR by virtue of its capacity to handle large and complex nonlinearly correlated data and derive meaningful information from it. This derived information is further utilized for forecasting GSR. Thus, for India, being a country of many climatologically and geographically different zones, approach of employing AI models in GSR prediction becomes very beneficial. This manuscript presents the various machine learning model approaches for GSR forecasting. Recent developments in this view are comprehensively and systematically reviewed considering the aspects like location, selection of input parameters, feature selection and model development. Current situation and future scope of research related to GSR forecasting accuracy improvement across the Indian regions is also discussed