Measurement based flow speed estimation for tidal turbine control

Luis Recalde-Camacho; Hong Yue

doi:10.1016/j.ifacol.2023.10.191

Measurement based flow speed estimation for tidal turbine control

Luis Recalde-Camacho, Hong Yue

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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Abstract

This work aims to explore effective online torque estimation techniques for tidal turbine control under varying flow conditions. A modified Kalman filter with adaptive features is developed to estimate hydrodynamic torque from a tidal turbine's available measurements, based on which a modified Newton-Rapson method is employed to calculate the effective flow speed. The rotor speed reference signal required for tidal turbine control can be produced using the estimated torque and flow speed. The Kalman filter model is constructed using on a low frequency lumped parameter model of a horizontal-axis, fixed-pitch, two-bladed variable speed tidal turbine, established from a fully characterised model of a real turbine. The adaptive feature of the Kalman filter allows the tracking of the spatial-temporal variations of the effective flow speed caused by turbulence. Simulation studies are implemented to test the developed algorithm over the full envelope of the flow speeds.

Original language	English
Title of host publication	22nd IFAC World Congress
Subtitle of host publication	Proceedings
Editors	Hideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
Place of Publication	Laxenburg
Pages	5419-5424
Number of pages	6
Volume	56-2
DOIs	https://doi.org/10.1016/j.ifacol.2023.10.191
Publication status	Published - 22 Nov 2023
Event	IFAC World Congress 2023: The 22nd World Congress of the International Federation of Automatic Control - Yokohama, Japan Duration: 9 Jul 2023 → 14 Jul 2023 Conference number: 22 https://www.ifac2023.org/

Publication series

Name	IFAC-PapersOnLine
Publisher	International Federation of Automatic Control (IFAC)
ISSN (Print)	2405-8963

Conference

Conference	IFAC World Congress 2023
Country/Territory	Japan
City	Yokohama
Period	9/07/23 → 14/07/23
Internet address	https://www.ifac2023.org/

Keywords

torque estimation
flow speed estimation
tidal turbine control
Kalman filtering techniques
Newton-Rapson method
tidal turbine modelling
time-varying disturbance

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Recalde-Camacho-Yue-IFAC-2023-Measurement-based-flow-speed-estimation-for-tidal-turbine-controlFinal published version, 927 KBLicence: CC BY-NC-ND 4.0

Cite this

@inproceedings{4ab36eaa095f4e7799a9b6ce6a114929,

title = "Measurement based flow speed estimation for tidal turbine control",

abstract = "This work aims to explore effective online torque estimation techniques for tidal turbine control under varying flow conditions. A modified Kalman filter with adaptive features is developed to estimate hydrodynamic torque from a tidal turbine's available measurements, based on which a modified Newton-Rapson method is employed to calculate the effective flow speed. The rotor speed reference signal required for tidal turbine control can be produced using the estimated torque and flow speed. The Kalman filter model is constructed using on a low frequency lumped parameter model of a horizontal-axis, fixed-pitch, two-bladed variable speed tidal turbine, established from a fully characterised model of a real turbine. The adaptive feature of the Kalman filter allows the tracking of the spatial-temporal variations of the effective flow speed caused by turbulence. Simulation studies are implemented to test the developed algorithm over the full envelope of the flow speeds.",

keywords = "torque estimation, flow speed estimation, tidal turbine control, Kalman filtering techniques, Newton-Rapson method, tidal turbine modelling, time-varying disturbance",

author = "Luis Recalde-Camacho and Hong Yue",

year = "2023",

month = nov,

day = "22",

doi = "10.1016/j.ifacol.2023.10.191",

language = "English",

volume = "56-2",

series = "IFAC-PapersOnLine",

publisher = "International Federation of Automatic Control (IFAC)",

pages = "5419--5424",

editor = "Hideaki Ishii and Yoshio Ebihara and Jun-ichi Imura and Masaki Yamakita",

booktitle = "22nd IFAC World Congress",

note = "IFAC World Congress 2023 : The 22nd World Congress of the International Federation of Automatic Control ; Conference date: 09-07-2023 Through 14-07-2023",

url = "https://www.ifac2023.org/",

}

TY - GEN

T1 - Measurement based flow speed estimation for tidal turbine control

AU - Recalde-Camacho, Luis

AU - Yue, Hong

N1 - Conference code: 22

PY - 2023/11/22

Y1 - 2023/11/22

N2 - This work aims to explore effective online torque estimation techniques for tidal turbine control under varying flow conditions. A modified Kalman filter with adaptive features is developed to estimate hydrodynamic torque from a tidal turbine's available measurements, based on which a modified Newton-Rapson method is employed to calculate the effective flow speed. The rotor speed reference signal required for tidal turbine control can be produced using the estimated torque and flow speed. The Kalman filter model is constructed using on a low frequency lumped parameter model of a horizontal-axis, fixed-pitch, two-bladed variable speed tidal turbine, established from a fully characterised model of a real turbine. The adaptive feature of the Kalman filter allows the tracking of the spatial-temporal variations of the effective flow speed caused by turbulence. Simulation studies are implemented to test the developed algorithm over the full envelope of the flow speeds.

AB - This work aims to explore effective online torque estimation techniques for tidal turbine control under varying flow conditions. A modified Kalman filter with adaptive features is developed to estimate hydrodynamic torque from a tidal turbine's available measurements, based on which a modified Newton-Rapson method is employed to calculate the effective flow speed. The rotor speed reference signal required for tidal turbine control can be produced using the estimated torque and flow speed. The Kalman filter model is constructed using on a low frequency lumped parameter model of a horizontal-axis, fixed-pitch, two-bladed variable speed tidal turbine, established from a fully characterised model of a real turbine. The adaptive feature of the Kalman filter allows the tracking of the spatial-temporal variations of the effective flow speed caused by turbulence. Simulation studies are implemented to test the developed algorithm over the full envelope of the flow speeds.

KW - torque estimation

KW - flow speed estimation

KW - tidal turbine control

KW - Kalman filtering techniques

KW - Newton-Rapson method

KW - tidal turbine modelling

KW - time-varying disturbance

U2 - 10.1016/j.ifacol.2023.10.191

DO - 10.1016/j.ifacol.2023.10.191

M3 - Conference contribution book

VL - 56-2

T3 - IFAC-PapersOnLine

SP - 5419

EP - 5424

BT - 22nd IFAC World Congress

A2 - Ishii, Hideaki

A2 - Ebihara, Yoshio

A2 - Imura, Jun-ichi

A2 - Yamakita, Masaki

CY - Laxenburg

T2 - IFAC World Congress 2023

Y2 - 9 July 2023 through 14 July 2023

ER -

Measurement based flow speed estimation for tidal turbine control

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