Artificial Intelligence Algorithms vs SVPWM for Optimal Performance of MLI Driving Three-Phase Machines

The performance of the three-phase multilevel inverter (MLI) is monitored and analyzed using genetic algorithm as an intelligent algorithm for solving mathematical equations accompanying the inverter operation. This performance is compared when employing the traditional space vector pulse width modulation (SVPWM) technique to drive the MLI. SVPWM is commonly used for applications in the power electronics field. The gating angles of the inverters are extracted using the selective harmonic elimination (SHE) concept for optimal switching using artificial algorithms and monitoring the performance of the inverter when loaded with a three-phase motor. Then monitoring the performance of the inverter when extracting these angles using SVPWM techniques. The inverter's voltages, currents, and load characteristics are analyzed, as well as the frequency analysis of the variables, while checking the active and reactive power levels injected to the load. A distinct advantage has been indicated for algorithmic technology compared to SVPWM technique for most variables. A detailed MATLAB model with reduced number of switches for three phase multilevel inverter is built and thoroughly analyzed for both techniques. Also, a practical 31 level single phase inverter is built for testing and measurement.