Neuro-Fuzzy Vector Control for Doubly-Fed Wind Driven Induction Generator

Abstract

Wound-rotor induction generator has numerous advantages in wind power generation over other types of generators. One scheme is realized when a converter cascade is used between the slip-ring terminals and the utility grid to control the rotor power. This configuration is called the doubly-fed induction generator (DFIG). A vector control scheme is developed to control the rotor side voltage source converter. This scheme allows the independent control of the generated active and reactive power as well as the rotor speed to track the maximum wind power point. In this work, a neuro-fuzzy gain tuner is proposed to control the DFIG. Vector control is used to allow independent control of the generator speed, active and reactive power. Six neuro-fuzzy gain tuners are used, two for each controlled variable. The input for each neuro-fuzzy system is the error value of speed, active or reactive power. The choice of only one input to the system simplifies the design and reduces the computational burden while giving excellent overall system performance.