Anomaly detection of a horizontal wind turbine using an extended kalman filter

Sung Ho Hur; Luis Recalde-Camacho; William E. Leithead

Anomaly detection of a horizontal wind turbine using an extended kalman filter

Sung Ho Hur
, Luis Recalde-Camacho
, William E. Leithead

School of Electronics Engineering

University of Strathclyde

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

3 Scopus citations

Abstract

Loads that have a disproportionate impact on the components and structure of a wind turbine can be induced by anomalies in the wind-field. For example, large unbalanced rotor loads could arise from blades sweeping through low level jets. The work presented in this paper proposes a novel anomaly detection scheme. Simulation results are presented demonstrating that it can be used to aid in the early detection of various anomalous conditions, such as mass imbalance, extreme wind shear and dynamic inflow, thereby allowing the wind turbine controllers to take appropriate diagnostic action to cope with such conditions.

Original language	English
Title of host publication	European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings
Editors	Sandrine Aubrun, Sandrine Aubrun, Jakob Mann
Publisher	European Wind Energy Association
ISBN (Electronic)	9782930670003
State	Published - 2015
Event	European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Paris, France Duration: 17 Nov 2015 → 20 Nov 2015

Publication series

Name	European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings

Conference

Conference	European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015
Country/Territory	France
City	Paris
Period	17/11/15 → 20/11/15

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Anomaly detection
Extended Kalman filter
Wind turbine control
Wind turbine monitoring

Cite this

Hur, S. H., Recalde-Camacho, L., & Leithead, W. E. (2015). Anomaly detection of a horizontal wind turbine using an extended kalman filter. In S. Aubrun, S. Aubrun, & J. Mann (Eds.), European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings (European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings). European Wind Energy Association.

Hur, Sung Ho ; Recalde-Camacho, Luis ; Leithead, William E. / Anomaly detection of a horizontal wind turbine using an extended kalman filter. European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings. editor / Sandrine Aubrun ; Sandrine Aubrun ; Jakob Mann. European Wind Energy Association, 2015. (European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings).

@inproceedings{555ad71aca0842069d487d6ad11f3179,

title = "Anomaly detection of a horizontal wind turbine using an extended kalman filter",

abstract = "Loads that have a disproportionate impact on the components and structure of a wind turbine can be induced by anomalies in the wind-field. For example, large unbalanced rotor loads could arise from blades sweeping through low level jets. The work presented in this paper proposes a novel anomaly detection scheme. Simulation results are presented demonstrating that it can be used to aid in the early detection of various anomalous conditions, such as mass imbalance, extreme wind shear and dynamic inflow, thereby allowing the wind turbine controllers to take appropriate diagnostic action to cope with such conditions.",

keywords = "Anomaly detection, Extended Kalman filter, Wind turbine control, Wind turbine monitoring",

author = "Hur, \{Sung Ho\} and Luis Recalde-Camacho and Leithead, \{William E.\}",

year = "2015",

language = "English",

series = "European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings",

publisher = "European Wind Energy Association",

editor = "Sandrine Aubrun and Sandrine Aubrun and Jakob Mann",

booktitle = "European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings",

note = "European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 ; Conference date: 17-11-2015 Through 20-11-2015",

}

Hur, SH, Recalde-Camacho, L & Leithead, WE 2015, Anomaly detection of a horizontal wind turbine using an extended kalman filter. in S Aubrun, S Aubrun & J Mann (eds), European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings. European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings, European Wind Energy Association, European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015, Paris, France, 17/11/15.

Anomaly detection of a horizontal wind turbine using an extended kalman filter. / Hur, Sung Ho; Recalde-Camacho, Luis; Leithead, William E.
European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings. ed. / Sandrine Aubrun; Sandrine Aubrun; Jakob Mann. European Wind Energy Association, 2015. (European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings).

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

TY - GEN

T1 - Anomaly detection of a horizontal wind turbine using an extended kalman filter

AU - Hur, Sung Ho

AU - Recalde-Camacho, Luis

AU - Leithead, William E.

PY - 2015

Y1 - 2015

N2 - Loads that have a disproportionate impact on the components and structure of a wind turbine can be induced by anomalies in the wind-field. For example, large unbalanced rotor loads could arise from blades sweeping through low level jets. The work presented in this paper proposes a novel anomaly detection scheme. Simulation results are presented demonstrating that it can be used to aid in the early detection of various anomalous conditions, such as mass imbalance, extreme wind shear and dynamic inflow, thereby allowing the wind turbine controllers to take appropriate diagnostic action to cope with such conditions.

AB - Loads that have a disproportionate impact on the components and structure of a wind turbine can be induced by anomalies in the wind-field. For example, large unbalanced rotor loads could arise from blades sweeping through low level jets. The work presented in this paper proposes a novel anomaly detection scheme. Simulation results are presented demonstrating that it can be used to aid in the early detection of various anomalous conditions, such as mass imbalance, extreme wind shear and dynamic inflow, thereby allowing the wind turbine controllers to take appropriate diagnostic action to cope with such conditions.

KW - Anomaly detection

KW - Extended Kalman filter

KW - Wind turbine control

KW - Wind turbine monitoring

UR - https://www.scopus.com/pages/publications/84995407297

M3 - Conference contribution

AN - SCOPUS:84995407297

T3 - European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings

BT - European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings

A2 - Aubrun, Sandrine

A2 - Mann, Jakob

PB - European Wind Energy Association

T2 - European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015

Y2 - 17 November 2015 through 20 November 2015

ER -

Hur SH, Recalde-Camacho L, Leithead WE. Anomaly detection of a horizontal wind turbine using an extended kalman filter. In Aubrun S, Aubrun S, Mann J, editors, European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings. European Wind Energy Association. 2015. (European Wind Energy Association Annual Conference and Exhibition 2015, EWEA 2015 - Scientific Proceedings).

Anomaly detection of a horizontal wind turbine using an extended kalman filter

Abstract

Publication series

Conference

UN SDGs

Keywords

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