Effective ANFIS-MPPT Control Technique for Standalone Photovoltaic Energy Generation

Artificial intelligence (AI) techniques are considered as an efficient way of controlling nonlinear systems. Among these methods, the most reliable is the adaptive neural fuzzy inference system (ANFIS). Because of that, many researchers use it in order to improve the available power of PV systems. So, this work studied the optimization and modeling of the PV system standalone based on an adaptive neural fuzzy inference technique. The system consists of PV modules used as a source to feed the load requirement, a boost converter used to step up the voltage of the system, a maximum power point tracker for extracting the maximum power from this system, and a DC load. Therefore, to show the effectiveness of the proposed method, we used Perturb and Observe as a conventional technique in order to compare it with the ANFIS technique's performances. The MATLAB/Simulink tool was used to validate the proposed system performances. The results of this study confirmed that the ANFIS technique has better behavior than P&O.