• D.Sharmila
• Dr. V. Maheshwari
• M.Murali
• Baladuraikannan P I D T

Solar energy is considered one of the most promising renewable sources due to the availability of sunlight and its cleaner performance compared to fossil fuels. The transferred energy from the sun to the earth changes during the day. So, absorbing the maximum energy from the solar panel and transferring it to the load is essential. Consequently, maximum power point tracking (MPPT) techniques are proposed in numerous research papers. In this paper, an adaptive neuro fuzzy inference system (ANFIS)-based MPPT controller has been introduced. To transfer maximum power to the load, the duty cycle of the high-gain dc-dc converter, which has been connected between the solar panel and the load, is used. The ANFIS controller combines the merits of neural networks and fuzzy logic. These controllers exhibit fast response and good efficiency in all weather conditions, making them more suitable for nonlinear systems like SPV modules. For validation, the proposed model was analyzed in different situations by hardware kit, and the results show the accuracy and high efficiency of the proposed tracker.

SPV Module, MPPT, ANFIS Controller, Driver, Converter.

"A HIGH GAIN HIGH VOLTAGE DC-DC CONVERTER WITH ANFIS CONTROLLER FOR PHOTO VOLTAIC APPLICATIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 10, page no.h553-h560, October-2023, Available :http://www.jetir.org/papers/JETIR2310669.pdf

"A HIGH GAIN HIGH VOLTAGE DC-DC CONVERTER WITH ANFIS CONTROLLER FOR PHOTO VOLTAIC APPLICATIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 10, page no. pph553-h560, October-2023, Available at : http://www.jetir.org/papers/JETIR2310669.pdf