Abstract
Neural network controller based induction generator for wind turbine applications
Highlights
The doubly fed induction generator (DFIG) can supply power at constant voltage and frequency, while the rotor speed varies
When a bidirectional AC-AC converter is used in the rotor circuit, the speed range can be extended above synchronous speed and power can be generated both from the stator and the rotor
An advantage of this type of (DFIG) drive is that the rotor converter need only to be rated for a fraction of the total output power, the fraction depends on the allowable sub and super synchronous speed range (Pena et al, 1996)
Summary
The doubly fed induction generator (DFIG) can supply power at constant voltage and frequency, while the rotor speed varies. This makes it suitable for variable speed wind energy application. The MATLAB function newff is used to create a three-layer tansig network with three inputs, namely the load resistance, load inductance and the machine speed, and two outputs, namely the rotor voltage and frequency. As this function finishes training at 500 epochs, Fig. 2 displays the following plot of errors (CybenkoG, 1989; Saerens & Soqetu, 1991; Magnus Nørgaard, 1997; Heikki & Koivo, 2000).
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