Enhancing Power Quality in Standalone Microgrids Powered by Wind and Battery Systems Using HO Algorithm Based Super Twisting Sliding Mode Controllers

This paper addresses the challenge of enhancing power quality in a standalone microgrid powered by wind and battery systems. Fluctuations in wind power generation and unpredictable electricity demand significantly impact power quality. To mitigate these issues, a control strategy utilizing Super Twisting Sliding Mode (STSM) controllers tuned by the Hippopotamus Optimization Algorithm (HOA) is proposed. The HOA algorithm efficiently determines optimal STSM controller parameters, leading to improved system performance and stability. A comparative study was conducted against PI, Fuzzy Logic controllers, and other metaheuristic optimization algorithms (PSO, GWO, WOA). Simulation results, obtained using MATLAB/Simulink, demonstrate the superior performance of the proposed methodology. Specifically, during a simulated abrupt load change, the system exhibited rapid recovery with frequency reaching equilibrium, significantly faster than PI and Fuzzy Logic controllers. Moreover, the DC link voltage remained stable with fluctuations of only 2%, while the three-phase RMS voltages at the Point of Load Bus (PLB) maintained balanced and stable values. These results confirm the enhanced power quality and robust operation achieved with the proposed HOA-tuned STSM control strategy, outperforming other tested methods. The methodology effectively manages both the energy management system and improves power quality in standalone wind and battery-powered microgrids.