Review on nanofluids and machine learning applications for thermoelectric energy conversion in renewable energy systems

Abstract

This review is about applications of nanofluids technology and different machine learning algorithms on the potential improvement of system performance and computational efficiency of thermo-electric device installed systems. Brief information about the thermo-electric energy conversion principles, construction materials and different application areas in energy system technologies are presented. The applications of nanofluid technology in thermoelectric conversion starting from the basic information on the common nanofluid types, modeling aspects and thermophysical properties are presented. Potential of using nanofluid in diverse thermoelectric installed system on the conversion efficiency and performance improvements are discussed. Applications of different machine learning algorithms with the basic information on the most common applied ones are presented. The computational efficiency of using different machine learning methods have been analyzed. The gap in the present literature and future trends are discussed. As thermoelectric devices, which are among the clean energy technologies, gain importance with the many advantages they offer and draw attention with their adaptability to different systems, the results summarized here, and future aspects will be beneficial for efficient design and optimization of energy related technologies.