| Title |
Neural Network Controller of A Grid-Connected Wind Energy Conversion System for Maximum Power Extraction |
| Authors |
Kyoung-Soo Ro ; Yeon-Sik Choo |
| Keywords |
wind energy conversion system(WECS) ; maximum power ; pitch control ; D/A inverter |
| Abstract |
This paper presents a neural network controller of a grid-connected wind energy conversion system for extracting maximum power from wind and a power controller to transfer the maximum power extracted into a utility grid. It discusses the modeling and simulation of the wind energy conversion system with the controllers, which consists of an induction generator, a transformer, a link of a rectifier, and an inverter. The paper describes the drive train model, induction generator model and grid-interface model for dynamics analysis. Maximum power extraction is achieved by controlling the pitch angle of the rotor blades by a neural network controller. Pitch control method is mechanically complicated, but the control performance is better than that of the stall regulation. The simulation results performed on MATLAB show the variation of the generator torque, the generator rotor speed, the pitch angle, and real/reactive power injected into the grid, etc. Based on the simulation results, the effectiveness of the proposed controllers is verified. |