An adaptive intelligent control of doubly fed wind generator for fast transient recovery

An adaptive radial basis function neural network based control has been proposed for a doubly fed induction generator connected to power system grid. The control is implemented on a capacitor energy stored device interfaced through a voltage source converter located at the generator terminal. The weights of the neural network are adapted online from the measurement of the generator speed and terminal voltage. Simulation results demonstrate that the adaptive intelligent control of the energy storage device can control the system transients effectively even under severely depressed voltage conditions. The radial basis neural network controller has the capability to learn very quickly to restore the system to normal operation smoothly.