Utilization of Data-Driven Methods in Solar Desalination Systems: A Comprehensive Review - Alhuyi Nazari, Mohammad; Salem, Mohamed; Mahariq, Ibrahim; Younes, Khaled; Maqableh, Bashar B. (Frontiers in Energy Research, 2021)
Renewable energy sources have been used for desalination in by employing different technologies and mediums due to the limitations of fossil fuels and the environmental issues related to their consumption. Solar energy is one of the most applicable types of renewable sources for desalination both in direct and indirect way. The performance of solar desalination is under effects of different factors which make their performance prediction difficult in some cases. In this regard, data-driven methods such as Artificial Neural Networks (ANNs) would be proper tool for their modeling and output forecasting. In the present article, a comprehensive review is provided on the applications of different data-driven approaches in performance modeling of solar-based desalination units. It can be concluded that by employing these method with proper inputs and structure, the outputs of the solar desalination units can be reliably and accurately forecasted. In addition, several recommendations are produced for the upcoming work in the relevant areas of the study.