Abstract
Due to the lack of inertia and uncertainty in the selection of optimal Proportional Integral (PI) controller gains, the voltage and frequency variations are higher in the islanded mode of the operation of a Microgrid (MG) compared to the grid-connected mode. This study, as such, develops an optimal control strategy for the voltage and frequency regulation of Photovoltaic (PV) based MG systems operating in islanding mode using Grasshopper Optimization Algorithm (GOA). The intelligence of the GOA is utilized to optimize the PI controller parameters. This ensures an enhanced dynamic response and power quality of the studied MG system during Distributed Generators (DG) insertion and load change conditions. A droop control is also employed within the control architecture, alongside the voltage and current control loops, as a power-sharing controller. In order to validate the performance of the proposed control architecture, its effectiveness in regulating MG voltage, frequency, and power quality is compared with the precedent Artificial Intelligence (AI) based control architectures for the same control objectives. The effectiveness of the proposed GOA based parameter selection method is also validated by analyzing its performance with respect to the improved transient response and power quality of the studied MG system in comparison with that of the Particle Swarm Optimization (PSO) and Whales Optimization Algorithm (WOA) based parameter selection methods. The simulation results establish that the GOA provides a faster and better solution than PSO and WOA which resulted in a minimum voltage and frequency overshoot with minimum output current and Total Harmonic Distortion (THD).
Highlights
The electricity demand is forecasted to increase significantly in the near future
The Grasshopper Optimization Algorithm (GOA) has been employed in this study for selecting the optimal values of Proportional Integral (PI) controllers in an islanded MG system by minimizing the given objective function
The results were subsequently compared with Whales Optimization Algorithm (WOA)- and Particle Swarm Optimization (PSO)-based controllers for the same operating conditions
Summary
The electricity demand is forecasted to increase significantly in the near future. In order to meet this projected demand, the rapid deployment of cost-effective and environment-friendly RenewableEnergy Sources is evident in different parts of the world. The electricity demand is forecasted to increase significantly in the near future. In order to meet this projected demand, the rapid deployment of cost-effective and environment-friendly Renewable. Energy Sources is evident in different parts of the world. Energy Sources (RES) for electricity generation, has further led to the development of small-scale power. 22 of small-scale power generating units called Microgrids with the aim of shifting partially certain loads generating units called. Microgrids of shifting certain loads from interconnected from interconnected power systemwith to a the newaim concept of thepartially distributed generation system. Power to a new of the adistributed system.by micro-sources such as wind A system. Microgrid (MG)concept is basically cluster ofgeneration loads supplied
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