Maximum power point tracking Algorithm Using ANFIS with Constant Power Generation Facility

A new algorithm based on Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is proposed in this paper for maximum power point tracking and constant power generation (MPPT-CPG) of PV modules. The proposed algorithm is investigated using PV module, DC-DC buck-boost converter, and a resistive load. Four input variable are used in the proposed algorithm, PV module's voltage, PV module's current, PV cell's temperature, and an input power limit variable. The power limit variable is the guidance of the proposed algorithm to work as an MPPT or to act as a CPG. If the power limit variable is higher than the maximum power of the PV module, the proposed algorithm tracks the available maximum power point (MPP). However, if the power limit is lower than the MPP, the proposed algorithm tracks the inserted power limit value. The proposed MPPT-CPG based ANFIS algorithm is modeled using MATLAB/SIMULINK. It is tested under disturbances in the weather conditions and under changing the power limit variable. The simulation results are presented to verify the proposed topology effectiveness and reliability.