Advances in Energy Research

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Additional power conservation in 200W power plant with the application of high thermal profiled cooling liquid & improved deep learning based maximum power point tracking algorithm

  • Raj G. Chauhan (Department of Electrical Engineering, Madhav Institute of Technology and Science) ;
  • Saurabh K. Rajput (Department of Electrical Engineering, Madhav Institute of Technology and Science) ;
  • Himmat Singh (Department of Electrical Engineering, Madhav Institute of Technology and Science)
  • Received : 2021.08.11
  • Accepted : 2022.09.09
  • Published : 2022.09.25
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Abstract

This research work focuses to design and simulate a 200W solar power system with electrical power conservation scheme as well as thermal power conservation modeling to improve power extraction from solar power plant. Many researchers have been already designed and developed different methods to extract maximum power while there were very researches are available on improving solar power thermally and mechanically. Thermal parameters are also important while discussing about maximizing power extraction of any power plant. A specific type of coolant which have very high boiling point is proposed to be use at the bottom surface of solar panel to reduce the temperature of panel in summer. A comparison between different maximum power point tracking (MPPT) technique and proposed MPPT technique is performed. Using this proposed Thermo-electrical MPPT (TE-MPPT) with Deep Learning Algorithm model 40% power is conserved as compared to traditional solar power system models.

Keywords

Acknowledgement

We thank Er. Arun Kumar Yadav (Researcher at Sapro Electronics & Electricals Ind. Pvt. Ltd.) for his assistance in EGW coolant data analysis and basic designing concepts of deep learning architecture in simulink.

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