Particle Swarm Optimization Algorithm Based Fuzzy Controller for Solid-State Transfer Switch Toward Fast Power Transfer and Power Quality Mitigation

The objective of this research is to propose an innovative method for improving the efficiency and productivity of fuzzy logic controllers (FLCs) under the influence of harmonics in non-linear loads, by using particle swarm optimization (PSO) for solid-state transfer switch (SSTS). A PSO-based FLC (PSOF) fitness function is introduced to optimize the load transfer performance by minimizing the mean squared error (MSE) in a short period of time. The traditional and time-consuming method of deriving membership functions (MFs) is avoided by utilizing adaptive MFs created from the fitness function evaluation results, which are incorporated into voltage error and rate of change of voltage error for input and output. A harmonic filter is employed to remove unwanted harmonic components generated by both linear and non-linear loads. The effectiveness of the proposed control system is evaluated with and without PSO, and the results demonstrate that optimization with PSO reduces transfer times by approximately 2 ms, 4.35 ms, 3.68 ms, and 3.56 ms for 100%, 50%, 25%, and 10%, respectively. The optimized fuzzy controller yields total transfer times of 0.5 ms, 8.72 ms, 7.88 ms, and 7.32 ms for 100%, 50%, 25%, and 10% voltage sag, respectively. Through simulation tests of the SSTS system, the accuracy and effectiveness of the developed FLC and design procedure are demonstrated. The optimized fuzzy controller shows superior performance in terms of transfer time, detection time, and harmonic reduction in comparison to those obtained without the PSO algorithm in all tested cases.