Performance analysis of ANFIS-PSO based grid integration using Improved SOGI-FLL Algorithm under fluctuating solar irradiance

This paper presents an integrated method of adaptive neuro-fuzzy inference system-particle swarm optimization (ANFIS–PSO) with an Improved Second Order Generalized Integrator-Frequency Locked Loop (ISOGI-FLL) to obtain a new MPPT strategy for achieving swift and maximum power tracking in PV systems with a reduced number of oscillations. The ANFIS-PSO approach does not require any additional sensors for measuring irradiance. The Improved Second order generalized integrator-frequency locked loop generates controlled signals for the voltage source converter (VSC). The presented approach is simulated in MATLAB/SIMULINK environment and its performance is validated with the steepest descent MPPT results.