Control of mechanical loads in wind turbines using an integrated aeroelastic model

Luis I. Minchala; Diego Cardenas-Fuentes; Oliver Probst

doi:10.1109/ISGT-LA.2017.8126732

Control of mechanical loads in wind turbines using an integrated aeroelastic model

Luis I. Minchala
, Diego Cardenas-Fuentes
, Oliver Probst

Instituto Tecnologico de Estudios Superiores de Monterrey

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

This paper presents the integration of an artificial neural network (ANN) based control algorithm for minimizing the stress of a wind turbine (WT) operating above-rated wind speeds, and a coupled aeroelastic model derived from structural blade element momentum (BEM) and thin-walled beam (TWB) theory. The coupled BEM/TWB model is used for real-Time determination of stress, strain and displacement in arbitrary positions of rotating blades. The controller selected is a proportionalintegral-derivate (PID) whose tuning parameters are calculated online through an Adaline ANN. The results show significant improvements in the stress reduction on the blades through the verification of a normalized stress factor. The stress reduction with the proposed control algorithm is up to 27%.

Original language	English
Title of host publication	2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781538633120
DOIs	https://doi.org/10.1109/ISGT-LA.2017.8126732
State	Published - 1 Dec 2017
Externally published	Yes
Event	2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017 - Quito, Ecuador Duration: 20 Sep 2017 → 22 Sep 2017

Publication series

Name	2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017
Volume	2017-January

Conference

Conference	2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017
Country/Territory	Ecuador
City	Quito
Period	20/09/17 → 22/09/17

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Aeroelastic model
Pitch control
Stress reduction
Wind turbine

Access to Document

10.1109/ISGT-LA.2017.8126732

Cite this

Minchala, L. I., Cardenas-Fuentes, D., & Probst, O. (2017). Control of mechanical loads in wind turbines using an integrated aeroelastic model. In 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017 (pp. 1-6). (2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT-LA.2017.8126732

Minchala, Luis I. ; Cardenas-Fuentes, Diego ; Probst, Oliver. / Control of mechanical loads in wind turbines using an integrated aeroelastic model. 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-6 (2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017).

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title = "Control of mechanical loads in wind turbines using an integrated aeroelastic model",

abstract = "This paper presents the integration of an artificial neural network (ANN) based control algorithm for minimizing the stress of a wind turbine (WT) operating above-rated wind speeds, and a coupled aeroelastic model derived from structural blade element momentum (BEM) and thin-walled beam (TWB) theory. The coupled BEM/TWB model is used for real-Time determination of stress, strain and displacement in arbitrary positions of rotating blades. The controller selected is a proportionalintegral-derivate (PID) whose tuning parameters are calculated online through an Adaline ANN. The results show significant improvements in the stress reduction on the blades through the verification of a normalized stress factor. The stress reduction with the proposed control algorithm is up to 27\%.",

keywords = "Aeroelastic model, Pitch control, Stress reduction, Wind turbine",

author = "Minchala, \{Luis I.\} and Diego Cardenas-Fuentes and Oliver Probst",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017 ; Conference date: 20-09-2017 Through 22-09-2017",

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Minchala, LI, Cardenas-Fuentes, D & Probst, O 2017, Control of mechanical loads in wind turbines using an integrated aeroelastic model. in 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017. 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017, Quito, Ecuador, 20/09/17. https://doi.org/10.1109/ISGT-LA.2017.8126732

Control of mechanical loads in wind turbines using an integrated aeroelastic model. / Minchala, Luis I.; Cardenas-Fuentes, Diego; Probst, Oliver.
2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-6 (2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Control of mechanical loads in wind turbines using an integrated aeroelastic model

AU - Minchala, Luis I.

AU - Cardenas-Fuentes, Diego

AU - Probst, Oliver

PY - 2017/12/1

Y1 - 2017/12/1

N2 - This paper presents the integration of an artificial neural network (ANN) based control algorithm for minimizing the stress of a wind turbine (WT) operating above-rated wind speeds, and a coupled aeroelastic model derived from structural blade element momentum (BEM) and thin-walled beam (TWB) theory. The coupled BEM/TWB model is used for real-Time determination of stress, strain and displacement in arbitrary positions of rotating blades. The controller selected is a proportionalintegral-derivate (PID) whose tuning parameters are calculated online through an Adaline ANN. The results show significant improvements in the stress reduction on the blades through the verification of a normalized stress factor. The stress reduction with the proposed control algorithm is up to 27%.

AB - This paper presents the integration of an artificial neural network (ANN) based control algorithm for minimizing the stress of a wind turbine (WT) operating above-rated wind speeds, and a coupled aeroelastic model derived from structural blade element momentum (BEM) and thin-walled beam (TWB) theory. The coupled BEM/TWB model is used for real-Time determination of stress, strain and displacement in arbitrary positions of rotating blades. The controller selected is a proportionalintegral-derivate (PID) whose tuning parameters are calculated online through an Adaline ANN. The results show significant improvements in the stress reduction on the blades through the verification of a normalized stress factor. The stress reduction with the proposed control algorithm is up to 27%.

KW - Aeroelastic model

KW - Pitch control

KW - Stress reduction

KW - Wind turbine

UR - https://www.scopus.com/pages/publications/85043475230

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DO - 10.1109/ISGT-LA.2017.8126732

M3 - Contribución a la conferencia

AN - SCOPUS:85043475230

T3 - 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017

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BT - 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 20 September 2017 through 22 September 2017

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Minchala LI, Cardenas-Fuentes D, Probst O. Control of mechanical loads in wind turbines using an integrated aeroelastic model. In 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-6. (2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017). doi: 10.1109/ISGT-LA.2017.8126732

Control of mechanical loads in wind turbines using an integrated aeroelastic model

Abstract

Publication series

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UN SDGs

Keywords

Access to Document

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