• Title/Summary/Keyword: Deep learning based MPPT

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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;Saurabh K. Rajput;Himmat Singh
    • Advances in Energy Research
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    • v.8 no.3
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    • pp.185-202
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    • 2022
  • 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.