Original scientific paper
https://doi.org/10.1080/00051144.2018.1455017
Output power levelling for DFIG wind turbine system using intelligent pitch angle control
Ehsan Hosseini
; Smart Microgrid Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Ghazanfar Shahgholian
; Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Abstract
Blade pitch angle control, as an indispensable part of wind turbine, plays a part in getting the desired power. In this regard, several pitch angle control methods have been proposed in order to limit aerodynamic power gained from the wind turbine system (WTS) in the high-windspeed regions. In this paper, intelligent control methods are applied to control the blade pitch angle of doubly-fed induction generator (DFIG) WTS. Conventional fuzzy logic and neuro-fuzzyparticle
swarm optimization controllers are used to get the appropriate wind power, where fuzzy inference system is based on fuzzy c-means clustering algorithm. It reduces the extra repetitive rules in fuzzy structure which in turn would reduce the complexity in neuro-fuzzy
network with maximizing efficiently. In comparing the controllers at any given wind speed, adaptive neuro-fuzzy inference systems controller involving both mechanical power and rotor speed revealed better performance to maintain the aerodynamic power and rotor speed at the
rated value. The effectiveness of the proposed method is verified by simulation results for a 9 MW DFIG WTS.
Keywords
Blade pitch angle control; ANFIS controller; fuzzy logic controller; PI controller
Hrčak ID:
203406
URI
Publication date:
18.6.2018.
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