Advanced Wind Energy Systems Operation and Maintenance Expertise

Informations projet

AWESOME

N° de convention de subvention: 642108

DOI 10.3030/642108

Projet clôturé

Date de signature de la CE 1 Decembre 2014

Date de début 1 Janvier 2015

Date de fin 31 Decembre 2018

Financé au titre de

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coût total € 2 862 074,16

Contribution de l’UE € 2 862 074,16

Coordonné par

FUNDACION CIRCE CENTRO DE INVESTIGACION DE RECURSOS Y CONSUMOS ENERGETICOS
Spain

Livrables

Websites, patent fillings, videos etc. (1)

AWESOME internet portal and first set of dissemination materials

A user friendly internet portal will be constructed, maintained and updated with relevant AWESOME information.

Documents, reports (4)

WP3 Final research report

Final report detailing the research activities carried out within the WP. This report will note progress against milestones and key research and training outputs. In addition publications and other tangible outputs will be referenced.

WP4 Final research report

Final report detailing the research activities carried out within the WP. This report will note progress against milestones and key research and training outputs. In addition publications and other tangible outputs will be referenced.

• Supervisory Board of the Network

description of the task, responsabilities of the supervisory Board of teh Network, including a list of members

WP5 Final research report

Final report detailing the research activities carried out within the WP. This report will note progress against milestones and key research and training outputs. In addition publications and other tangible outputs will be referenced.

Publications

Peer reviewed articles (34)

Wind Turbine Failures - Tackling current Problems in Failure Data Analysis

Auteurs: M D Reder, E Gonzalez, J J Melero
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 072027, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/7/072027

SCADA alarms processing for wind turbine component failure detection

Auteurs: E Gonzalez, M Reder, J J Melero
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 072019, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/7/072019

Probability density function selection based on the characteristics of wind speed data

Auteurs: N Y Yürüşen, Julio J Melero
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 032067, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/3/032067

Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization

Auteurs: Filippo Campagnolo, Vlaho Petrović, Johannes Schreiber, Emmanouil M. Nanos, Alessandro Croce, Carlo L. Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 032006, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/3/032006

Comparative analysis of binning and Gaussian Process based blade pitch angle curve of a wind turbine for the purpose of condition monitoring

Auteurs: Ravi Kumar Pandit, David Infield
Publié dans: Journal of Physics: Conference Series, Numéro 1102, 2018, Page(s) 012037, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/1102/1/012037

Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy

Auteurs: Ravi Kumar Pandit, David Infield, James Carroll
Publié dans: Wind Energy, 2018, Page(s) 302-315, ISSN 1095-4244
Éditeur: John Wiley & Sons Inc.
DOI: 10.1002/we.2285

Gaussian Process Operational Curves for Wind Turbine Condition Monitoring

Auteurs: Ravi Pandit, David Infield
Publié dans: Energies, Numéro 11/7, 2018, Page(s) 1631, ISSN 1996-1073
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/en11071631

SCADA-based wind turbine anomaly detection using Gaussian process models for wind turbine condition monitoring purposes

Auteurs: Ravi Kumar Pandit, David Infield
Publié dans: IET Renewable Power Generation, Numéro 12/11, 2018, Page(s) 1249-1255, ISSN 1752-1416
Éditeur: Institution of Engineering and Technology
DOI: 10.1049/iet-rpg.2018.0156

Performance assessment of a wind turbine using SCADA based Gaussian Process model

Auteurs: Pandit, Ravi Kumar; Infield, David
Publié dans: International Journal of Prognostics and Health Management 9(1), Numéro 2, 2018, ISSN 2153-2648
Éditeur: PHM Society
DOI: 10.5281/zenodo.1295522

Very short-term forecast of near-coastal flow using scanning lidars

Auteurs: Laura Valldecabres, Alfredo Peña, Michael Courtney, Lueder von Bremen, Martin Kühn
Publié dans: Wind Energy Science, Numéro 3/1, 2018, Page(s) 313-327, ISSN 2366-7451
Éditeur: Copernicus Publications
DOI: 10.5194/wes-3-313-2018

Key Performance Indicators for Wind Farm Operation and Maintenance

Auteurs: Elena Gonzalez, Emmanouil M. Nanos, Helene Seyr, Laura Valldecabres, Nurseda Y. Yürüşen, Ursula Smolka, Michael Muskulus, Julio J. Melero
Publié dans: Energy Procedia, Numéro 137, 2017, Page(s) 559-570, ISSN 1876-6102
Éditeur: Elsevier Ltd.
DOI: 10.1016/j.egypro.2017.10.385

Very short-term probabilistic forecasting of wind power based on dual-Doppler radar measurements in the North Sea

Auteurs: L Valldecabres, NG Nygaard, L von Bremen, M Kühn
Publié dans: Journal of Physics: Conference Series, Numéro 1037, 2018, Page(s) 052010, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/1037/5/052010

On the Use of Dual-Doppler Radar Measurements for Very Short-Term Wind Power Forecasts

Auteurs: Laura Valldecabres, Nicolai Nygaard, Luis Vera-Tudela, Lueder von Bremen, Martin Kühn
Publié dans: Remote Sensing, Numéro 10/11, 2018, Page(s) 1701, ISSN 2072-4292
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/rs10111701

Design of a multipurpose scaled wind turbine model

Auteurs: E M Nanos, N Kheirallah, F Campagnolo, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 1037, 2018, Page(s) 052016, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/1037/5/052016

Verification and Calibration of a Reduced Order Wind Farm Model by Wind Tunnel Experiments

Auteurs: J Schreiber, E M Nanos, F Campagnolo, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 854, 2017, Page(s) 012041, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/854/1/012041

Numerical and Experimental Study of Wake Redirection Techniques in a Boundary Layer Wind Tunnel

Auteurs: J Wang, S Foley, E M Nanos, T Yu, F Campagnolo, C L Bottasso, A Zanotti, A Croce
Publié dans: Journal of Physics: Conference Series, Numéro 854, 2017, Page(s) 012048, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/854/1/012048

Stereo particle image velocimetry set up for measurements in the wake of scaled wind turbines

Auteurs: Gabriele Campanardi, Donato Grassi, Alex Zanotti, Emmanouil M Nanos, Filippo Campagnolo, Alessandro Croce, Carlo L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 882, 2017, Page(s) 012003, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/882/1/012003

Lifetime extension for large offshore wind farms: Is it enough to reassess fatigue for selected design positions?

Auteurs: Corantin Bouty, Sebastian Schafhirt, Lisa Ziegler, Michael Muskulus
Publié dans: Energy Procedia, Numéro 137, 2017, Page(s) 523-530, ISSN 1876-6102
Éditeur: Elsevier
DOI: 10.1016/j.egypro.2017.10.381

Lifetime extension of onshore wind turbines: A review covering Germany, Spain, Denmark, and the UK

Auteurs: Lisa Ziegler, Elena Gonzalez, Tim Rubert, Ursula Smolka, Julio J. Melero
Publié dans: Renewable and Sustainable Energy Reviews, Numéro 82, 2018, Page(s) 1261-1271, ISSN 1364-0321
Éditeur: Elsevier BV
DOI: 10.1016/j.rser.2017.09.100

Fatigue Crack Detection for Lifetime Extension of Monopile-based Offshore Wind Turbines

Auteurs: Jutta Stutzmann, Lisa Ziegler, Michael Muskulus
Publié dans: Energy Procedia, Numéro 137, 2017, Page(s) 143-151, ISSN 1876-6102
Éditeur: Elsevier
DOI: 10.1016/j.egypro.2017.10.341

Design optimization with genetic algorithms: How does steel mass increase if offshore wind monopiles are designed for a longer service life?

Auteurs: Lisa Ziegler, Matthieu Rhomberg, Michael Muskulus
Publié dans: Journal of Physics: Conference Series, Numéro 1104, 2018, Page(s) 012014, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/1104/1/012014

Using SCADA data for wind turbine condition monitoring – a review

Auteurs: Jannis Tautz-Weinert, Simon J. Watson
Publié dans: IET Renewable Power Generation, 2016, ISSN 1752-1416
Éditeur: Institution of Engineering and Technology
DOI: 10.1049/iet-rpg.2016.0248

Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection

Auteurs: J Tautz-Weinert, S J Watson
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 072014, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/7/072014

Optimisation of Data Acquisition in Wind Turbines with Data-Driven Conversion Functions for Sensor Measurements

Auteurs: L. Colone, M. Reder, J. Tautz-Weinert, J.J. Melero, A. Natarajan, S.J. Watson
Publié dans: Energy Procedia, Numéro 137, 2017, Page(s) 571-578, ISSN 1876-6102
Éditeur: Elsevier
DOI: 10.1016/j.egypro.2017.10.386

Statistical Evaluation of SCADA data for Wind Turbine Condition Monitoring and Farm Assessment

Auteurs: E Gonzalez, J Tautz-Weinert, J J Melero, S J Watson
Publié dans: Journal of Physics: Conference Series, Numéro 1037, 2018, Page(s) 032038, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/1037/3/032038

The Financial Benefits of Various Catastrophic Failure Prevention Strategies in a Wind Farm: Two market studies (UK-Spain)

Auteurs: N Y Yürüşen, J Tautz-Weinert, S J Watson, J J Melero
Publié dans: Journal of Physics: Conference Series, Numéro 926, 2017, Page(s) 012014, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/926/1/012014

Spatial-temporal analysis of coherent offshore wind field structures measured by scanning Doppler-lidar

Auteurs: L Valldecabres, W Friedrichs, L von Bremen, M Kühn
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 072028, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/7/072028

Fatigue reassessment for lifetime extension of offshore wind monopile substructures

Auteurs: Lisa Ziegler, Michael Muskulus
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 092010, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/9/092010

Effect of Load Sequence and Weather Seasonality on Fatigue Crack Growth for Monopile-based Offshore Wind Turbines

Auteurs: Lisa Ziegler, Sebastian Schafhirt, Matti Scheu, Michael Muskulus
Publié dans: Energy Procedia, Numéro 94, 2016, Page(s) 115-123, ISSN 1876-6102
Éditeur: Elsevier
DOI: 10.1016/j.egypro.2016.09.204

Sensitivity of Wave Fatigue Loads on Offshore Wind Turbines under Varying Site Conditions

Auteurs: Lisa Ziegler, Sven Voormeeren, Sebastian Schafhirt, Michael Muskulus
Publié dans: Energy Procedia, Numéro 80, 2015, Page(s) 193-200, ISSN 1876-6102
Éditeur: Elsevier
DOI: 10.1016/j.egypro.2015.11.422

Value of information of repair times for offshore wind farm maintenance planning

Auteurs: Helene Seyr, Michael Muskulus
Publié dans: Journal of Physics: Conference Series, Numéro 753, 2016, Page(s) 092009, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/753/9/092009

Safety Indicators for the Marine Operations in the Installation and Operating Phase of an Offshore Wind Farm

Auteurs: Helene Seyr, Michael Muskulus
Publié dans: Energy Procedia, Numéro 94, 2016, Page(s) 72-81, ISSN 1876-6102
Éditeur: Elsevier
DOI: 10.1016/j.egypro.2016.09.200

Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring

Auteurs: Ravi Kumar Pandit, David Infield
Publié dans: International Journal of Energy and Environmental Engineering, Numéro 10/2, 2019, Page(s) 181-188, ISSN 2008-9163
Éditeur: Springer Science + Business Media
DOI: 10.1007/s40095-018-0287-3

Brief communication: Structural monitoring for lifetime extension of offshore wind monopiles: can strain measurements at one level tell us everything?

Auteurs: Lisa Ziegler, Ursula Smolka, Nicolai Cosack, Michael Muskulus
Publié dans: Wind Energy Science, Numéro 2/2, 2017, Page(s) 469-476, ISSN 2366-7451
Éditeur: Copernicus Publications
DOI: 10.5194/wes-2-469-2017

Other (1)

Comparison of binned and Gaussian Process based power curves for condition monitoring purposes

Auteurs: Ravi Kumar Pandit, David Infield.
Publié dans: Journal of Maintenance Engineering, 2017, Page(s) 293-305
Éditeur: ShieldCrest

Conference proceedings (10)

Comparative analysis of binning and support vector regression for wind turbine rotor speed based power curve use in condition monitoring

Auteurs: Ravi Pandit, David Infield
Publié dans: 2018 53rd International Universities Power Engineering Conference (UPEC), 2018, Page(s) 1-6, ISBN 978-1-5386-2910-9
Éditeur: IEEE
DOI: 10.1109/upec.2018.8542057

QQ plot for assessment of Gaussian Process predicted power curve error distribution function

Auteurs: Ravi Kumar Pandit, David Infield.
Publié dans: The European Workshop on Structural Health Monitoring Series (EWSHM) conference proceedings, 2018
Éditeur: NDT.net

Using Gaussian process theory for wind turbine power curve analysis with emphasis on the confidence intervals

Auteurs: Ravi Kumar Pandit, David Infield
Publié dans: 2017 6th International Conference on Clean Electrical Power (ICCEP), 2017, Page(s) 744-749, ISBN 978-1-5090-4682-9
Éditeur: IEEE
DOI: 10.1109/ICCEP.2017.8004774

Wake Characterization of a Multipurpose Scaled Wind Turbine Model

Auteurs: Emmanouil Nanos, Johanne Robke, Florian Heckmeier, Kyle Jones, Michael Cerny, Giacomo Valerio Iungo, Carlo L. Bottasso
Publié dans: AIAA Scitech 2019 Forum, 2019, ISBN 978-1-62410-578-4
Éditeur: American Institute of Aeronautics and Astronautics
DOI: 10.2514/6.2019-2082

Neural Networks for Wind Turbine Fault Detection via Current Signature Analysis

Auteurs: R K Ibrahim, J Tautz-Weinert, SJ Watson
Publié dans: WindEurope Summit 2016, 2016
Éditeur: WindEurope

Challenges in using operational data for reliable wind turbine condition monitoring

Auteurs: Jannis Tautz-Weinert, Simon J. Watson
Publié dans: Proceedings of Annual International Ocean (Offshore) and Polar Engineering Conference (ISOPE), 2017
Éditeur: © International Society of Offshore and Polar Engineers (ISOPE)

Combining model-based monitoring and a physics of failure approach for wind turbine failure detection

Auteurs: Jannis Tautz-Weinert, Simon J. Watson
Publié dans: 30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017), 2017
Éditeur: © University of Central Lancashire

Condition monitoring of wind turbine drive trains by normal behaviour modelling of temperatures

Auteurs: Jannis Tautz-Weinert, Simon J. Watson
Publié dans: Proceedings Conference for Wind Power Drives 2017, 2017
Éditeur: © Dirk Abel, Christian Brecher, Rik W. De Doncker, Kay Hameyer, Georg Jacobs, Antonello Monti, Wolfgang Schröder

Condition monitoring by neural network modelling of drive train temperature

Auteurs: Jannis Tautz-Weinert, Simon J. Watson
Publié dans: European Academy of Wind Energy, 2016
Éditeur: European Academy of Wind Energy

Comparing a Fracture Mechanics Model to the SN-Curve Approach for Jacket-Supported Offshore Wind Turbines: Challenges and Opportunities for Lifetime Prediction

Auteurs: Lisa Ziegler, Michael Muskulus
Publié dans: Volume 6: Ocean Space Utilization; Ocean Renewable Energy, 2016, Page(s) V006T09A054, ISBN 978-0-7918-4997-2
Éditeur: ASME
DOI: 10.1115/OMAE2016-54915

Thesis and dissertations (1)

Improved wind turbine monitoring using operational data

Auteurs: Jannis Tautz-Weinert
Publié dans: 2018
Éditeur: Loughborough University