DFIG with Adaptive Control using B-spline Neural Networks

摘要

The doubly fed induction generator enables better use of wind energy, but it is necessary to have an adequate control scheme that achieves optimum performance in steady state and transient condition. The paper aim is to show that using B-spline neural networks,the electrical grid including wind energy systemscan achieve satisfactory operation. The control structure is based on a back to backarrangement where the interest variables are regulated by PI linear controllers. However, to deal with the nonlinear and uncertain system conditionswe proposed that the control parameters are updated online.The main task is that the power converters operation adapt by itself during the grid changes. The basic problem consists of tuning the PI controllers simultaneously when the system and load are subjected to disturbances. The applicability of the proposal is demonstrated by simulation in a three-node grid, where one end is an infinite bus and the other connects the wind system, between them there are two transmission lines. Results exhibit that the proposed controllers' tuning is comparable to that obtained by a conventional design, without requiring a detailed model.