Doubly-Fed Induction Generator Drive System Based on Maximum Power Curve Searching using Fuzzy Logic Controller

This paper proposes a novel variable speed control algorithm for a grid connected doubly-fed induction generator (DFIG) system. The main objective is to track the maximum power curve characteristic by using an adaptive fuzzy logic controller, and to compare it with the conventional optimal torque control method for large inertia wind turbines. The role of the FLC is to adapt the transfer function of the harvested mechanical power controller according to the operating point in variable wind speed. The control system has two sub-systems for the rotor side and the grid side converters (RSC, GSC). Active and reactive power control of the back-to-back converters has been achieved indirectly by controlling q-axis and d-axis current components. The main function of the RSC controllers is to track the maximum power through controlling the electromagnetic torque of the wind turbine. The GSC controls the DC-link voltage, and guarantees unity power factor between the GSC and the grid. The proposed system is developed and tested in MATLAB/SimPowerSystem (SPS) environment.

• doubly fed induction generator
• wind turbines
• maximum power point tracking
• fuzzy logic controller
• variable speed control
• rotor side converter
• grid-side converter
• back-to-back converter
• active and reactive power control
• DC bus voltage regulation
• unity power factor
• optimal torque control

• 7 — Affordable and clean energy
• 9 — Industry, innovation and infrastructure

• Wind Turbine Control Systems
• Sensorless Control of Electric Motors
• Electric Motor Design and Analysis
• doubly fed induction generator
• wind turbines
• maximum power point tracking
• fuzzy logic controller
• variable speed control
• rotor side converter
• grid-side converter
• back-to-back converter
• Electrical and Electronic Engineering
• Engineering