Integral Gain Selection using Genetic Algorithms for a Doubly-Fed Induction Generator

Warachart Sae-Kok and Somyot Kaitwanidvilai


DFIG, Genetic Algorithms, Pole placement controller


This paper aims at application of genetic algorithms to select integral gain of pole-placement with integral action controller for a doubly-fed induction generator (DFIG). Uncertainty from the wind and the grid disturbance can occur to the applied system resulting in reduced operating performance. Therefore, high performance controller should be applied to this system. However, due to the steady state error caused by lack of uncertainty compensation while using the simple pole placement controller, the integral gain is applied to solve this problem. The application and tuning for the integral gain are proposed in this paper. The simulation and result analysis are then shown to prove that this controller is suitable to the DFIG system.

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