Pv/T Systems For Energy Efficiency By Using Advanced Deep Neural Network (DNN) And Nanofluid In Solar Systems

Abstract

Today, solar energy is a very popular alternative energy source due to its enormous availability in nature. In this study, focusing on the electro-mechanical production industry of advanced PV/T solar panels, studies carried out on the development of new methodological methods for the efficiency of existing asset management practices of the infrastructure of this industry and the optimal improvement. For this, it is to integrate a power-generating PV/T panel and a solar thermal heating panel within the same collection surface. PV/T systems are one of the subjects that scientific studies have focused on in recent years. The main reasons for this are to increase the electricity generation performance of PVs, as well as to obtain thermally hot fluid from the system. In this research, it was implemented using a new roof-mounted PV/T multi-reflection panel, which not only increases the power output of the PV/T panel, but most importantly, the aesthetic aspect is a major barrier to large-scale uptake of PV/TIn this study, we developed a new advanced MPPT (maximum power point tracking) algorithm such as Deep Neural Network (DNN) controller especially for photovoltaic system. The proposed DNN based MPPT algorithm is developed PV/T voltage, current and corresponding duty cycle.