A Novel PSO Based Fuzzy Controller for Robust Operation of Solid-State Transfer Switch and Fast Load Transfer in Power Systems

Abstract

This paper proposes a novel particle swarm optimization (PSO) algorithm based fuzzy logic controller (FLC) for improving the performance of automatic solid-state transfer switch (SSTS) with respect to transfer time. The proposed technique generates adaptive membership functions (MFs) of voltage error and rate of change of voltage error for input and output based on the fitness function formulated by the PSO. An optimal PSO-based FLC (PSOF) fitness function is further employed to tune and minimize the mean absolute error (MAE) to improve the performance of the load transfer in a short duration. Results obtained from the proposed PSOF are compared with those obtained with the conventional FLC to validate the developed controller. It is observed that the proposed PSOF optimized controller can transfer the load faster than the conventional FLC controller. The accuracy of the developed PSOF is illustrated and investigated via simulation tests for SSTS in the IEEE 9-bus system. It can be concluded that the PSOF controller is better than the only fuzzy controller in all tested cases in terms of transfer time.INDEX TERMS Automatic solid-state transfer switch, fuzzy control, optimization algorithm, power transfer, load transfer, power system faults.

Dynamic Voltage Stability Enhancement in Electric Vehicle Battery Charger Using Particle Swarm Optimization

“…The PSO approach is an evolutionary optimization method inspired by flocks of birds and schools of fish. It is often implemented in various engineering applications due to its superior computational efficiency [40][41][42]. The PSO approach converges faster and more consistently than other populationbased stochastic optimization approaches, such as the genetic algorithm (GA) and ant colony optimization (ACO) [30,31,33,[43][44][45].…”