LIDAR-based wind speed modelling and control system design

Research output: Contribution to conferenceProceeding

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Abstract

Abstract—The main objective of this work is to explore the feasibility of using LIght Detection And Ranging (LIDAR) measurement and develop feedforward control strategy to improve wind turbine operation. Firstly the Pseudo LIDAR measurement data is produced using software package GH Bladed across a distance from the turbine to the wind measurement points. Next the transfer function representing the evolution of wind speed is developed. Based on this wind evolution model, a model-inverse feedforward control strategy is employed for the pitch control at above-rated wind conditions, in which LIDAR measured wind speed is fed into the feedforward. Finally the baseline feedback controller is augmented by the developed feedforward control. This control system is developed based on a Supergen 5MW wind turbine model linearised at the operating point, but tested with the nonlinear model of the same system. The system performances with and without the feedforward control channel are compared. Simulation results suggest that with LIDAR information, the added feedforward control has the potential to reduce blade and tower loads in comparison to a baseline feedback control alone.
Original languageEnglish
Pages1-6
Number of pages6
Publication statusPublished - 11 Sep 2015
Event21st IEEE International Conference on Automation and Computing (ICAC 2015) - University of Strathclyde, Glasgow, United Kingdom
Duration: 11 Sep 201512 Sep 2015

Conference

Conference21st IEEE International Conference on Automation and Computing (ICAC 2015)
CountryUnited Kingdom
CityGlasgow
Period11/09/1512/09/15

Fingerprint

feedforward control
control systems design
Feedforward control
control system
wind velocity
Systems analysis
Control systems
wind turbine
wind turbines
modeling
Wind turbines
wind measurement
transfer function
turbine
towers
turbines
blades
feedback control
Software packages
transfer functions

Keywords

  • wind turbine control
  • light Detection And Ranging (LiDAR)
  • disturbance rejection
  • wind speed evolution
  • feedforward control

Cite this

Wang, M., Yue, H., Bao, J., & Leithead, W. E. (2015). LIDAR-based wind speed modelling and control system design. 1-6. 21st IEEE International Conference on Automation and Computing (ICAC 2015), Glasgow, United Kingdom.
Wang, Mengling ; Yue, Hong ; Bao, Jie ; Leithead, William E. / LIDAR-based wind speed modelling and control system design. 21st IEEE International Conference on Automation and Computing (ICAC 2015), Glasgow, United Kingdom.6 p.
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title = "LIDAR-based wind speed modelling and control system design",
abstract = "Abstract—The main objective of this work is to explore the feasibility of using LIght Detection And Ranging (LIDAR) measurement and develop feedforward control strategy to improve wind turbine operation. Firstly the Pseudo LIDAR measurement data is produced using software package GH Bladed across a distance from the turbine to the wind measurement points. Next the transfer function representing the evolution of wind speed is developed. Based on this wind evolution model, a model-inverse feedforward control strategy is employed for the pitch control at above-rated wind conditions, in which LIDAR measured wind speed is fed into the feedforward. Finally the baseline feedback controller is augmented by the developed feedforward control. This control system is developed based on a Supergen 5MW wind turbine model linearised at the operating point, but tested with the nonlinear model of the same system. The system performances with and without the feedforward control channel are compared. Simulation results suggest that with LIDAR information, the added feedforward control has the potential to reduce blade and tower loads in comparison to a baseline feedback control alone.",
keywords = "wind turbine control, light Detection And Ranging (LiDAR), disturbance rejection, wind speed evolution, feedforward control",
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note = "21st IEEE International Conference on Automation and Computing (ICAC 2015) ; Conference date: 11-09-2015 Through 12-09-2015",

}

Wang, M, Yue, H, Bao, J & Leithead, WE 2015, 'LIDAR-based wind speed modelling and control system design' 21st IEEE International Conference on Automation and Computing (ICAC 2015), Glasgow, United Kingdom, 11/09/15 - 12/09/15, pp. 1-6.

LIDAR-based wind speed modelling and control system design. / Wang, Mengling; Yue, Hong; Bao, Jie; Leithead, William E.

2015. 1-6 21st IEEE International Conference on Automation and Computing (ICAC 2015), Glasgow, United Kingdom.

Research output: Contribution to conferenceProceeding

TY - CONF

T1 - LIDAR-based wind speed modelling and control system design

AU - Wang, Mengling

AU - Yue, Hong

AU - Bao, Jie

AU - Leithead, William E.

PY - 2015/9/11

Y1 - 2015/9/11

N2 - Abstract—The main objective of this work is to explore the feasibility of using LIght Detection And Ranging (LIDAR) measurement and develop feedforward control strategy to improve wind turbine operation. Firstly the Pseudo LIDAR measurement data is produced using software package GH Bladed across a distance from the turbine to the wind measurement points. Next the transfer function representing the evolution of wind speed is developed. Based on this wind evolution model, a model-inverse feedforward control strategy is employed for the pitch control at above-rated wind conditions, in which LIDAR measured wind speed is fed into the feedforward. Finally the baseline feedback controller is augmented by the developed feedforward control. This control system is developed based on a Supergen 5MW wind turbine model linearised at the operating point, but tested with the nonlinear model of the same system. The system performances with and without the feedforward control channel are compared. Simulation results suggest that with LIDAR information, the added feedforward control has the potential to reduce blade and tower loads in comparison to a baseline feedback control alone.

AB - Abstract—The main objective of this work is to explore the feasibility of using LIght Detection And Ranging (LIDAR) measurement and develop feedforward control strategy to improve wind turbine operation. Firstly the Pseudo LIDAR measurement data is produced using software package GH Bladed across a distance from the turbine to the wind measurement points. Next the transfer function representing the evolution of wind speed is developed. Based on this wind evolution model, a model-inverse feedforward control strategy is employed for the pitch control at above-rated wind conditions, in which LIDAR measured wind speed is fed into the feedforward. Finally the baseline feedback controller is augmented by the developed feedforward control. This control system is developed based on a Supergen 5MW wind turbine model linearised at the operating point, but tested with the nonlinear model of the same system. The system performances with and without the feedforward control channel are compared. Simulation results suggest that with LIDAR information, the added feedforward control has the potential to reduce blade and tower loads in comparison to a baseline feedback control alone.

KW - wind turbine control

KW - light Detection And Ranging (LiDAR)

KW - disturbance rejection

KW - wind speed evolution

KW - feedforward control

UR - http://csee.essex.ac.uk/ICAC2015/

M3 - Proceeding

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ER -

Wang M, Yue H, Bao J, Leithead WE. LIDAR-based wind speed modelling and control system design. 2015. 21st IEEE International Conference on Automation and Computing (ICAC 2015), Glasgow, United Kingdom.