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. 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.

Keywords

• PV/T
• MPPT
• DNN
• Türkiye
• İran
• Nanofluid

Supporting Institution

Türkiye Scholarships I Research Programme (YTB)

Project Number

22ır013805

Thanks

The authors sincerely thank Türkiye Scholarships (22IR013805 )number research fellowship programme(YTB) and Kastamonu University and Gazi University Energy Central Laboratory staff for helping

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