ANFIS-PSO-Based Optimization for THD Reduction in Cascaded Multilevel Inverter UPS Systems

Uninterruptible Power Supplies (UPSs) protect electronic equipment by delivering consistent power. Among the core components of a UPS is the inverter, which converts stored DC energy from batteries into AC power. This work focuses on a cascaded multilevel inverter topology for its ability to reduce voltage Total Harmonic Distortion (THD), which is essential for maintaining UPS efficiency and power quality. Using an ANFIS (Adaptive Neuro-Fuzzy Inference System) model, enhanced with the Particle Swarm Optimization (PSO) algorithm, the switching angles were optimized to minimize THD. This work focused on an online UPS with a seven-level inverter structure powered by three LifePo4 S17 batteries, with critical load levels (100%, 95%, 50%, 15%, and 5%) represented in 35 experimental cases. The experimental design allowed the ANFIS-PSO model to adapt to varying voltages, achieving robust THD reduction. The results demonstrated that this combination of ANFIS and PSO provided effective angle optimization, with a low standard deviation of 0.06 between the training and simulated %THD, highlighting the process’s accuracy. The analysis showed that, in most cases, the simulated THD values closely aligned with, or even improved upon, the calculated values, with discrepancies not exceeding 0.2%. These findings support the ANFIS-PSO model’s potential in enhancing power electronics applications, particularly in critical sectors like renewable energy and power transmission, where THD minimization is crucial.