A Deep Learning Approach for Mppt in Solar Pv System

Researchers are increasingly interested in renewable energy due to its environmental benefits and abundance. Solar photovoltaics (PV) are frequently utilized to generate electricity from sunlight. One major challenge in solar PV power generation is identifying peak output from different operational sites. To determine the maximum power point (MPP) using solar PV characteristic curves, an appropriate MPPT method is necessary. Traditional MPPT methods are commonly used due to their simplicity, despite the availability of many other options. Traditional methods may struggle to handle abrupt variations in sun irradiation and temperature. This study employs a LSTM-based MPPT controller technique to measure maximum power from solar PV. This study compares the performance of a PV system with the proposed MPPT module and alternative controllers under similar climatic and operational circumstances. The deep learning-based controller achieved the maximum efficiency of up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 6. 6 \%}$</tex>.