PSO-ANFIS Controlled Multi Level Inverter for Integration of Renewable Energy Sources with Smart Grid

Abstract

Pollution-free electricity generation is possible due to the use of Renewable Energy Sources (RES).
Integration of hybrid renewable energy sources (solar and wind system) and smart grid through
Cascaded H bridge five level inverter is deal with help of PSO-ANFIS controller in our proposed work.
Proposed works explains an artificial intelligence based Total Harmonic Distortion (THD) of MultiLevel Inverters (MLI). Proposed controller is combination of Particle Swarm Optimization (PSO) and
Adaptive Neuro Fuzzy Inference System (ANFIS). Reference voltage and grid voltage are input of
ANFIS to give harmonic-free control output. Training stage of ANFIS optimized by PSO to handle
switching angle of MLI and generate harmonic-less control voltage. This work is implemented in
Matlab/Simulink platform to evaluate THD performance of proposed work. Performance of PSOANFIS is compared with Artificial Neural Network (ANN), ANFIS and GA-ANFIS in terms of error
convergence. THD of 0.25% (with PSO-ANFIS) and 34.31% (without controller) is achieved in
proposed system when compared with PI, FLC and ALO-NN controllers