Experimental Validation of an Eleven Level Symmetrical Inverter Using Genetic Algorithm and Queen Bee Assisted Genetic Algorithm for Solar Photovoltaic Applications

This paper presents an 11-level symmetrical inverter with reduced number of semiconductor switches for the solar photovoltaic (PV) applications. The genetic algorithm (GA) and queen bee assisted genetic algorithm (QBAGA) are performing a major task for the proposed Multilevel Inverter (MLI). The proposed symmetrical MLI topology has reduced number of semiconductor devices compared to the conventional MLI. However, the modulation index threshold related to the drop in the number of inverter output voltage levels is higher than that of the MLI. The objective of this paper is to find the optimal value of modulation index (m(a)) using optimization algorithms in order to attain the maximum power point (MPP) from the solar PV array. An 11-level symmetrical inverter is taken into consideration whose optimal modulation index (m(a)) is calculated in order to eliminate the harmonics. The total harmonic distortion (THD) measurement is used to estimate the quality of inverter the output voltage which implies the improvement of power quality. The simulations are carried out in MATLAB/Simulink and the experimental prototype is implemented with field programmable gate array (FPGA)-based processor. The simulation and experimental results show lesser THD with the absence of filter components which expose the effectiveness of the proposed system.