Control of wind turbines using nonlinear adaptive field excitation algorithms

Y. D. SONG; B. DHINAKARAN; X. BAO

doi:10.1109/acc.2000.879461

Control of wind turbines using nonlinear adaptive field excitation algorithms

Y. D. SONG^*
, B. DHINAKARAN
, X. BAO

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

20 Citations (Scopus)

Abstract

Automatic control represents one of the most important factors responsible for the efficiency and reliability of wind power conversion systems. Thus far, only a few isolated applications of conventional control to wind power systems have appeared in the literature. To make wind power generation truly cost-effective and reliable, advanced control techniques are imperative. In this paper, we develop a control scheme for wind turbines using nonlinear and adaptive control theory. Based on both mechanical and electrical dynamics, nonlinear and adaptive control algorithms are derived to on-line adjust the excitation winding voltage of the generator. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by both analysis and computer simulation. © 2000 AACC.

Original language	English
Title of host publication	Proceedings of the 2000 American Control Conference
Publisher	IEEE
Pages	1551-1555
Number of pages	5
Volume	3
DOIs	https://doi.org/10.1109/acc.2000.879461
Publication status	Published - 2000
Externally published	Yes

Publication series

Name	Proceedings of the American Control Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISSN (Print)	0743-1619

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Adaptive control
Nonlinear control
Stability
Variable speed control
Wind turbines

Access to Document

10.1109/acc.2000.879461

Cite this

@inproceedings{d022ff702205468aaad4bd19ae7b9ca5,

title = "Control of wind turbines using nonlinear adaptive field excitation algorithms",

abstract = "Automatic control represents one of the most important factors responsible for the efficiency and reliability of wind power conversion systems. Thus far, only a few isolated applications of conventional control to wind power systems have appeared in the literature. To make wind power generation truly cost-effective and reliable, advanced control techniques are imperative. In this paper, we develop a control scheme for wind turbines using nonlinear and adaptive control theory. Based on both mechanical and electrical dynamics, nonlinear and adaptive control algorithms are derived to on-line adjust the excitation winding voltage of the generator. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by both analysis and computer simulation. {\textcopyright} 2000 AACC.",

keywords = "Adaptive control, Nonlinear control, Stability, Variable speed control, Wind turbines",

author = "SONG, \{Y. D.\} and B. DHINAKARAN and X. BAO",

year = "2000",

doi = "10.1109/acc.2000.879461",

language = "English",

volume = "3",

series = "Proceedings of the American Control Conference",

publisher = "IEEE",

pages = "1551--1555",

booktitle = "Proceedings of the 2000 American Control Conference",

}

Control of wind turbines using nonlinear adaptive field excitation algorithms. / SONG, Y. D.; DHINAKARAN, B.; BAO, X.
Proceedings of the 2000 American Control Conference. Vol. 3 IEEE, 2000. p. 1551-1555 (Proceedings of the American Control Conference).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Control of wind turbines using nonlinear adaptive field excitation algorithms

AU - SONG, Y. D.

AU - DHINAKARAN, B.

AU - BAO, X.

PY - 2000

Y1 - 2000

N2 - Automatic control represents one of the most important factors responsible for the efficiency and reliability of wind power conversion systems. Thus far, only a few isolated applications of conventional control to wind power systems have appeared in the literature. To make wind power generation truly cost-effective and reliable, advanced control techniques are imperative. In this paper, we develop a control scheme for wind turbines using nonlinear and adaptive control theory. Based on both mechanical and electrical dynamics, nonlinear and adaptive control algorithms are derived to on-line adjust the excitation winding voltage of the generator. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by both analysis and computer simulation. © 2000 AACC.

AB - Automatic control represents one of the most important factors responsible for the efficiency and reliability of wind power conversion systems. Thus far, only a few isolated applications of conventional control to wind power systems have appeared in the literature. To make wind power generation truly cost-effective and reliable, advanced control techniques are imperative. In this paper, we develop a control scheme for wind turbines using nonlinear and adaptive control theory. Based on both mechanical and electrical dynamics, nonlinear and adaptive control algorithms are derived to on-line adjust the excitation winding voltage of the generator. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by both analysis and computer simulation. © 2000 AACC.

KW - Adaptive control

KW - Nonlinear control

KW - Stability

KW - Variable speed control

KW - Wind turbines

UR - https://www.scopus.com/pages/publications/0034539195

U2 - 10.1109/acc.2000.879461

DO - 10.1109/acc.2000.879461

M3 - Conference paper (refereed)

AN - SCOPUS:0034539195

VL - 3

T3 - Proceedings of the American Control Conference

SP - 1551

EP - 1555

BT - Proceedings of the 2000 American Control Conference

PB - IEEE

ER -

Control of wind turbines using nonlinear adaptive field excitation algorithms

Abstract

Publication series

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this