Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

Abstract

The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not share any connection with the utility grid. Hence, a proper control architecture of islanded MG is essential to control the voltage and frequency, including the power quality and optimal transient response during different operating conditions. Therefore, this study proposes an intelligent and robust controller for islanded MG, which can accomplish the above-mentioned tasks with the optimal transient response and power quality. The proposed controller utilizes the droop control in addition to the back to back proportional plus integral (PI) regulator-based voltage and current controllers in order to accomplish the mentioned control objectives efficiently. Furthermore, the intelligence of the one of the most modern soft computational optimization algorithms called salp swarm optimization algorithm (SSA) is utilized to select the best combination of the PI gains (kp and ki) and dc side capacitance (C), which in turn ensures optimal transient response during the distributed generator (DG) insertion and load change conditions. Finally, to evaluate the effectiveness of the proposed control approach, its outcomes are compared with that of the previous approaches used in recent literature on basis of transient response measures, quality of solution and power quality. The results prove the superiority of the proposed control scheme over that of the particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA) based MG controllers for the same operating conditions and system configuration.