Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG)

Xue Fei WANG; Yong Duan SONG; Dan Yong LI; Kai ZHANG; Shan XUE; Ming QIN

doi:10.1007/978-3-642-31362-2_60

Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG)

Xue Fei WANG^*
, Yong Duan SONG
, Dan Yong LI
, Kai ZHANG
, Shan XUE
, Ming QIN

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Wind power as a renewable energy source is irregular in occurrence. It is interesting yet challenging to maximize the energy capture from wind. Most existing control methods for wind power generation are traditionally based on wind turbine with fixed ratio gear box. In this work we investigate the control problem of wind power conversion by wind turbine with Variable-Ratio-Gearbox (VRG). In this setting, a permanent magnet synchronous motor (PMSM) unit is embedded into the system to enhance the generated power quality. This is achieved by regulating the PMSM speed properly to maintain constant (synchronous) speed of the generator over wide range of wind speed. Model-independent control algorithms are developed based on neuroadaptive backstepping approach. Both theoretical analysis and numerical simulation confirm that the proposed control scheme is able to ensure high precision motor speed tracking in the presence of parameter uncertainties and external load disturbances. © 2012 Springer-Verlag.

Original language	English
Title of host publication	Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings
Editors	Jun WANG, Gary G. YEN, Marios M. POLYCARPOU
Publisher	Springer Berlin Heidelberg
Pages	544-554
Number of pages	11
ISBN (Electronic)	9783642313622
ISBN (Print)	9783642313615
DOIs	https://doi.org/10.1007/978-3-642-31362-2_60
Publication status	Published - 2012
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Berlin, Heidelberg
Volume	7368
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Neuroadaptive Control
PMSM
Speed Regulation
Wind Turbine

Access to Document

10.1007/978-3-642-31362-2_60

Cite this

WANG, X. F., SONG, Y. D., LI, D. Y., ZHANG, K., XUE, S., & QIN, M. (2012). Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG). In J. WANG, G. G. YEN, & M. M. POLYCARPOU (Eds.), Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings (pp. 544-554). (Lecture Notes in Computer Science; Vol. 7368). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_60

WANG, Xue Fei ; SONG, Yong Duan ; LI, Dan Yong et al. / Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG). Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings. editor / Jun WANG ; Gary G. YEN ; Marios M. POLYCARPOU. Springer Berlin Heidelberg, 2012. pp. 544-554 (Lecture Notes in Computer Science).

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title = "Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG)",

abstract = "Wind power as a renewable energy source is irregular in occurrence. It is interesting yet challenging to maximize the energy capture from wind. Most existing control methods for wind power generation are traditionally based on wind turbine with fixed ratio gear box. In this work we investigate the control problem of wind power conversion by wind turbine with Variable-Ratio-Gearbox (VRG). In this setting, a permanent magnet synchronous motor (PMSM) unit is embedded into the system to enhance the generated power quality. This is achieved by regulating the PMSM speed properly to maintain constant (synchronous) speed of the generator over wide range of wind speed. Model-independent control algorithms are developed based on neuroadaptive backstepping approach. Both theoretical analysis and numerical simulation confirm that the proposed control scheme is able to ensure high precision motor speed tracking in the presence of parameter uncertainties and external load disturbances. {\textcopyright} 2012 Springer-Verlag.",

keywords = "Neuroadaptive Control, PMSM, Speed Regulation, Wind Turbine",

author = "WANG, \{Xue Fei\} and SONG, \{Yong Duan\} and LI, \{Dan Yong\} and Kai ZHANG and Shan XUE and Ming QIN",

year = "2012",

doi = "10.1007/978-3-642-31362-2\_60",

language = "English",

isbn = "9783642313615",

series = "Lecture Notes in Computer Science",

publisher = "Springer Berlin Heidelberg",

pages = "544--554",

editor = "Jun WANG and YEN, \{Gary G.\} and POLYCARPOU, \{Marios M.\}",

booktitle = "Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings",

}

WANG, XF, SONG, YD, LI, DY, ZHANG, K, XUE, S & QIN, M 2012, Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG). in J WANG, GG YEN & MM POLYCARPOU (eds), Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings. Lecture Notes in Computer Science, vol. 7368, Springer Berlin Heidelberg, pp. 544-554. https://doi.org/10.1007/978-3-642-31362-2_60

Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG). / WANG, Xue Fei; SONG, Yong Duan; LI, Dan Yong et al.
Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings. ed. / Jun WANG; Gary G. YEN; Marios M. POLYCARPOU. Springer Berlin Heidelberg, 2012. p. 544-554 (Lecture Notes in Computer Science; Vol. 7368).

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

TY - GEN

T1 - Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG)

AU - WANG, Xue Fei

AU - SONG, Yong Duan

AU - LI, Dan Yong

AU - ZHANG, Kai

AU - XUE, Shan

AU - QIN, Ming

PY - 2012

Y1 - 2012

N2 - Wind power as a renewable energy source is irregular in occurrence. It is interesting yet challenging to maximize the energy capture from wind. Most existing control methods for wind power generation are traditionally based on wind turbine with fixed ratio gear box. In this work we investigate the control problem of wind power conversion by wind turbine with Variable-Ratio-Gearbox (VRG). In this setting, a permanent magnet synchronous motor (PMSM) unit is embedded into the system to enhance the generated power quality. This is achieved by regulating the PMSM speed properly to maintain constant (synchronous) speed of the generator over wide range of wind speed. Model-independent control algorithms are developed based on neuroadaptive backstepping approach. Both theoretical analysis and numerical simulation confirm that the proposed control scheme is able to ensure high precision motor speed tracking in the presence of parameter uncertainties and external load disturbances. © 2012 Springer-Verlag.

AB - Wind power as a renewable energy source is irregular in occurrence. It is interesting yet challenging to maximize the energy capture from wind. Most existing control methods for wind power generation are traditionally based on wind turbine with fixed ratio gear box. In this work we investigate the control problem of wind power conversion by wind turbine with Variable-Ratio-Gearbox (VRG). In this setting, a permanent magnet synchronous motor (PMSM) unit is embedded into the system to enhance the generated power quality. This is achieved by regulating the PMSM speed properly to maintain constant (synchronous) speed of the generator over wide range of wind speed. Model-independent control algorithms are developed based on neuroadaptive backstepping approach. Both theoretical analysis and numerical simulation confirm that the proposed control scheme is able to ensure high precision motor speed tracking in the presence of parameter uncertainties and external load disturbances. © 2012 Springer-Verlag.

KW - Neuroadaptive Control

KW - PMSM

KW - Speed Regulation

KW - Wind Turbine

UR - https://www.scopus.com/pages/publications/84865151231

U2 - 10.1007/978-3-642-31362-2_60

DO - 10.1007/978-3-642-31362-2_60

M3 - Conference paper (refereed)

AN - SCOPUS:84865151231

SN - 9783642313615

T3 - Lecture Notes in Computer Science

SP - 544

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BT - Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings

A2 - WANG, Jun

A2 - YEN, Gary G.

A2 - POLYCARPOU, Marios M.

PB - Springer Berlin Heidelberg

ER -

WANG XF, SONG YD, LI DY, ZHANG K, XUE S, QIN M. Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG). In WANG J, YEN GG, POLYCARPOU MM, editors, Advances in Neural Networks, ISNN 2012: 9th International Symposium on Neural Networks, Proceedings. Springer Berlin Heidelberg. 2012. p. 544-554. (Lecture Notes in Computer Science). doi: 10.1007/978-3-642-31362-2_60

Neuroadaptive speed assistance control of wind turbine with Variable Ratio Gearbox (VRG)

Abstract

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UN SDGs

Keywords

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