Abstract
The solar photovoltaic energy is becoming popular in the modern-day distribution networks due to the clean energy factor. The photovoltaic modules exhibit a nonlinearity in the output power concerning the environmental conditions. This work suggests an adaptive neuro-fuzzy inference system- (ANFIS-) based maximal power point tracker (MPPT) for the optimization of the solar photovoltaic system (SPVS). The controller modelled is utilized to optimize the output power of a DC-DC converter connected to a 400 W PV array. The entire model is analysed employing MATLAB/SIMULINK using primary features provided by the technical data. The behavior of the controller modelled is tested for various weather conditions and partial shading conditions. The findings show the controller’s tracking speed effectiveness and dynamic response in PSCs.