GA-lookup table based firing angle optimization method for a PV connected CHB-MLI

This paper presents the implementation of an artificial intelligence strategy genetic algorithm (GA) in the photovoltaic (PV) connected cascaded h-bridge multilevel inverter (CHB-MLI). In the presence of the worst maximum power point (MPP) due to temperature or irradiance mismatches, a voltage imbalance condition occurs in the PV systems. Here, genetic algorithm is used to find the most optimized firing angles for different equal and unequal dc voltages of the three bridges at which minimum harmonics will be present in the system. For the partially shaded condition, the voltage variation is about 10-20%, in this paper 20% voltage variation has been considered and the total harmonic distortion (THD) is being used as an evaluation criteria to quantify the results. The %THD obtained by applying GA are shown in the look-up table and simulations are performed in the MATLAB/SIMULINK environment.