Dynamic modeling and optimal control of DFIG wind energy systems using DFT and NSGA-II

• Once a DFIG is subjected to a disturbance by a change in the wind speed, the stator flux cannot change instantly.
• The most popular and practical control scheme of DFIGs is still field-oriented control based on PI controllers.
• Considering small signal stability, the main purpose of the control system is to increase the system damping ratio as well as to guarantee enough stability margin.
• This paper introduces an optimization technique based on NSGA-II incorporating DFT analysis to achieve better control performance for DFIG system stability.

Once a doubly-fed induction generator (DFIG) is subjected to a disturbance by a change in the wind speed, the stator flux cannot change instantly. Under this condition, rotor back-EMF voltages reflect the effects of stator dynamics on rotor current dynamics, and have an important role on the oscillations of the rotor current. These oscillations decrease the DFIG system reliability and gear lifetime. Moreover, by focusing only on small signal analysis, the dynamic damping performance immediately following such disturbances is often degraded. Additional improvement in performance will be achieved if discrete Fourier transform (DFT) is used to quantify damping characteristic of the rotor current during changes of the operating points. This paper introduces an optimization technique based on non-dominated sorting genetic algorithm-II (NSGA-II) incorporating DFT analysis to achieve better control performance for DFIG system stability. Considering small signal stability, the main purpose of the control system in the present paper is to increase the system damping ratio as well as to guarantee enough stability margin. Eigenvalue analysis and time-domain simulations have been presented to demonstrate that the proposed optimizing method yields better control performance in comparison with one designed using mere eigenvalue relocation.