Optimizing Control Performance and Reliability of Hybrid Renewable Systems with Fuzzy Logic Controller

Abstract

The growing distribution of hybrid renewable energy systems (HRES) comprising photovoltaic (PV) and wind energy sources has raised serious challenges for power quality and system reliability due to irregular and nonlinear nature of renewable generation. The conventional Atom Search Optimization (ASO)-based controllers have shown effective optimization capability; however, their practical implementation is limited by high computational complexity, sensitivity to initialization, and limited compliance in rapidly changing operating situations. This paper presents an improved Fuzzy Logic Controller (FLC) for better control performance and reliability of grid-connected HRES. The controller is formulated on a rule-based fuzzy inference scheme to control the system dynamics without employing computationally expensive optimization procedures, thus enabling fast real-time response and robust operation under uncertain environmental and load conditions. The controller is validated in detailed MATLAB/Simulink simulations in different irradiance, wind speed and load disturbance. The simulation shows that the proposed FLC enhances the voltage stability, reduces the harmonic distortion, improves the dynamic response and reduces the computational burden when compared with the conventional ASO based controller. So, the presented approach is capable and computationally feasible for enhancing the operational reliability and power quality of grid-connected HRES.