A Deep Learning Approach for MPPT of PV System: Design and Comparison

Interest in renewable energy sources is expanding as an inevitable consequence of reducing global warming and the limited amount of fossil fuels. Solar and wind energy are among the most important sources of renewable energy, especially in rural areas. The energy generated by photovoltaic panels is affected by weather and operational conditions. Therefore, studies have been conducted to improve the efficiency of photovoltaic power plants by developing maximum power point tracking (MPPT) modules. This paper presents the design of a deep learning based MPPT controller. It provides a comparison of the performance of the PV system when using the proposed MPPT module and when using other controllers in the same climate and operating conditions. The results showed that the deep learning-based controller has the highest efficiency of up to 99.6%.