Solar Radiation Estimation for Renewable Energy Artificial Intelligence

The many techniques for estimating solar radiation, including empirical models, time series, artificial intelligence algorithms, and hybrid models, will all be thoroughly reviewed in this review article. Accurate understanding of solar radiation data is widely accepted as being essential to maximizing its advantages in a variety of fields, including agriculture, energy production, heat, health, and tourism. The study will assess each model's performance success in various places and emphasize its benefits and drawbacks. Also highlighted will be the research gaps, obstacles, and future prospects in solar radiation estimate. We shall underline that empirical models are preferred for their usability and inexpensive computing costs, although hybrid models typically tend to produce more accurate findings. The article will also discuss how crucial it is to estimate solar radiation while taking into account atmospheric, geographic, climatic, and historical data. To anticipate solar radiation in a certain area more precisely, this knowledge is crucial. The paper will also discuss the difficulties researchers have while choosing the best model and how to solve these difficulties. The study will also emphasize how important it is to carry out further research in this field in order to improve the precision of solar radiation estimation and its influence on sustainable development. Researchers, stakeholders, and policymakers may use the review to get important information that will help them decide how to use solar radiation for sustainable development. In the end, the article will give a thorough summary of the related work for estimating solar radiation and point out potential areas for further investigation.