0
Research Papers

Intelligent Control of a Large Variable Speed Wind Turbine

[+] Author and Article Information
Mohammad A. Ayoubi

Li-Chou Tai

 Department of Mechanical Engineering, Santa Clara University, CA 95053-0575 LTai@scu.com

J. Sol. Energy Eng 134(1), 011001 (Nov 01, 2011) (8 pages) doi:10.1115/1.4004979 History: Received October 09, 2010; Revised August 11, 2011; Published November 01, 2011; Online November 01, 2011

We present two intelligent controllers for large and flexible wind turbines operating in high-speed winds, a Fuzzy-P + I and an adaptive neuro-fuzzy controller. The control objective is to regulate the rotor speed at the given rated power in region 3 (full load) via collective blade pitch angle. The modeled turbine is a three-bladed, upwind machine with a flexible blade and tower. We use the particle swarm optimization method in off-line training for our adaptive neuro-fuzzy controller. Numerical simulations are performed using wind inflow step change with a set of input–output data of a nonlinear wind turbine model. We compare the performance of the proposed controllers with the baseline PI-controller. Simulation results confirm successful performance of the proposed controllers.

Copyright © 2012 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Figure 1

Structure of fuzzy-P + I controller

Grahic Jump Location
Figure 2

Fuzzy-P membership functions

Grahic Jump Location
Figure 3

Input–output behavior of fuzzy-P

Grahic Jump Location
Figure 4

PSO optimizer with ANFIS controller for wind turbine rotor speed regulation

Grahic Jump Location
Figure 5

Structure of PSO optimizer with ANFIS controller

Grahic Jump Location
Figure 6

ANFIS-P membership functions

Grahic Jump Location
Figure 7

Input–output behavior of ANFIS-P

Grahic Jump Location
Figure 8

ANFIS-I membership functions

Grahic Jump Location
Figure 9

Input–output behavior of ANFIS-I

Grahic Jump Location
Figure 10

Sugeno fuzzy-model with two inputs [28]

Grahic Jump Location
Figure 11

Equivalent ANFIS architecture with two inputs and one output [28]

Grahic Jump Location
Figure 12

simulink model of FAST with ANFIS controller in the loop

Grahic Jump Location
Figure 13

Step wind profile

Grahic Jump Location
Figure 14

Blade pitch angle for baseline-PI, fuzzy-P + I, and ANFIS controllers

Grahic Jump Location
Figure 15

Tower-top forward-after deflection with baseline-PI, fuzzy-P + I, and ANFIS controllers

Grahic Jump Location
Figure 16

Blade 1 flap deflection with baseline-PI, fuzzy-P + I, and ANFIS controllers

Grahic Jump Location
Figure 17

LSS torque with baseline-PI, fuzzy-P + I, and ANFIS controllers

Grahic Jump Location
Figure 18

Rotor speed regulation with baseline-PI, fuzzy-P + I, and ANFIS controllers

Grahic Jump Location
Figure 19

Wind test profile No. 1

Grahic Jump Location
Figure 20

Wind test profile No. 2

Grahic Jump Location
Figure 21

Rotor speed regulation of CART3 with baseline-PI, fuzzy-P + I, and ANFIS controllers for wind test profile No. 1

Grahic Jump Location
Figure 22

Rotor speed regulation of CART3 with baseline-PI, fuzzy-P + I, and ANFIS controllers for wind test profile No. 2

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In