A Fuzzy Logic Controlled Variable Step-Size P&O MPPT Method For Wind Turbines

This study evaluates the performance of a Fuzzy Logic-Based Variable Step Perturb and Observe (FLC-VS P&O) MPPT algorithm in a wind-battery supported DC micro-grid operating in islanded mode. The proposed method is assessed in terms of voltage stability, maximum power tracking accuracy, and wind energy utilization efficiency. Comparative simulations are performed against three conventional control strategies (PI control, classical P&O, and variable step-size P&O) to evaluate the performance of the proposed FLC-VS P&O algorithm. The microgrid system consists of a permanent magnet synchronous generator (PMSG)-based wind turbine, a bidirectional DC-DC converter-connected battery, and a common DC bus structure. In the FLC-VS P&O MPPT approach, triangular membership functions dynamically adjust the step size based on power and voltage variations, while decisions are made using the Mamdani inference method. Simulation results demonstrate that the proposed FLC-VS P&O controller achieves a higher average power output, faster transient recovery, and improved DC bus voltage regulation compared to classical and variable step-size $\mathrm{P} \& \mathrm{O}$ algorithms. Among all tested configurations, the proposed FLC-VS P&O algorithm provides the highest average power output while sustaining voltage regulation. These findings indicate that the proposed method offers an effective, stable, and embedded-system-compatible MPPT solution for islanded DC microgrids powered by wind energy. Unlike conventional MPPT methods, the proposed algorithm combines fuzzy logic-based dynamic step sizing with a low-complexity structure, offering a novel and embedded-compatible solution tailored for wind-battery islanded microgrids.