Thursday, 29 September 2016
11:30 - 13:00 Component reliability and diagnostics: early detection and intervention is key!
O&M & logistics  
          

This session will give an insight into wind turbine reliability and the state of the art in wind turbine diagnostics. It will look at how to collect and analyse reliability data in order to improve design as well as O&M strategies. This session will also look at the use of supervisory control and data acquisition (SCADA) data for condition monitoring: both 'conventional' ten minute data and higher frequency 1Hz data. Finally, there will be a case study of how power data from the converter can be used to infer wind turbine loading.

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Co-chair(s):

Berthold Hahn Fraunhofer IWES, Germany
Co-authors:
Hahn Berthold (1) ^F Faulstich Stefan (1) Welte Thomas (2) Conaill Soraghan (3) O Connor Frank (4) van Bussel Gerard (5) Bangalore Pramod (7) Sorensen John Dalagaard (6) Asgarpour Masoud (8) Pettersson Lasse (9) Vatn Jorn (10) Karlson Benjamin (11)
(1) Fraunhofer IWES, Kassel, Germany (2) SINTEF Foundation for Scientific and Industrial Research, Trondheim, Norway (3) Offshore Renewable Energy Catapult, Blyth, United Kingdom (4) ServusNet Informatics, Cork, Ireland (5) Delft University of Technology, Delft, The Netherlands (6) DTU / University Aalborg, Aalborg, Denmark (7) Chalmers University , Gothenburg, Sweden (8) ECN Energy research Centre of the Netherlands, Petten, The Netherlands (9) Vattenfall Sweden, Stockholm, Sweden (10) NTNU University Trondheim, Trondheim, Norway (11) Sandia National Labs, Albuquerque, United States of America

Recommended practices for data collection, reliability assessment and O&M optimisation

Introduction

The increasing future demands on reliability and profitability of wind energy use, especially offshore, require the optimization of wind-turbine maintenance. For this in turn, appropriate data management and sophisticated decision-support tools are prerequisites. Especially owners/operators strive at optimizing maintenance effort versus availability and Life Cycle Cost. Thus, their demand on decision support by Key Performance Indicators and other information from historical O&M data is the main driver for identifying the right data sets to record.
Several working groups on appropriate standards for operation and maintenance of wind power plants have been launched on national levels for onshore wind energy application, e. g. joint activities on standardizing operation and maintenance measures, documentation and data structure. However, up to now there is no comprehensive guideline or standard to refer to. So results of existing initiatives are nearly not comparable and also data cannot get compiled and analyzed commonly.

Approach

The IEA Task 33 ‘Reliability Data – Standardization of Data Collection for Wind Turbine Reliability and Operation Maintenance Analyses’ is dealing with standardized, well-structured databases for optimizing reliability and maintenance procedures. The aim is to address the different developments of data collection and failure statistic and to agree on standards and overall structures.
The purpose is to bring together the present actors in the industry and research community to create synergies and agreements in the many R&D activities already on-going in the field of statistical failure analysis. The work in Task 33 started in October 2012. In total 22 different companies and institutes from 9 different countries were actively involved in the task.
IEA Wind Task 33 aims at supporting reliability improvement and optimizing operation and maintenance (O&M) procedures of wind turbines through analyses of reliability data. The Task 33 team has compiled a joint document, which will be published as the “Recommended Practices for Data Collection, reliability Assessment and O&M Optimization” in September 2016.

Main body of abstract

In general, all stakeholders in the wind industry strive for utilizing experience from O&M of wind turbines for supporting future decisions and activities. Operators aim at improving maintenance efforts. Owners look for ensuring their future investments. OEM and component suppliers aim at improving their products. Financiers and insurers go for reducing their risks. However, the whole wind industry could benefit from O&M experience, but individual experience is often not systematically prepared and thus no universally valid information are available.
Mainly for the operators there is a large potential for optimizing data collection and preparing analyses results. They have access to the needed data and they can directly benefit from analyses results. If there was a common understanding on how to and if an operator had defined his individual purposes and decided for certain assessments, he could derive what raw data to collect and how to treat it.
Therefore, the Recommended Practices for Data Collection, Reliability Assessment and O&M Optimization deal with typical methods and analyses, appropriate taxonomies for data categorization and systematically collected datasets.

Conclusion

In the end, ‘IEA Wind Recommended Practices’ shall provide the final results of the task to the wind industry. They explain the different possibilities for utilizing reliability and maintenance data and it will give guidelines on how to proceed for different individual scopes. It describes
• the motivation for using reliability data in the field of maintenance,
• typical maintenance strategies and maintenance tasks,
• statistical analyses, their opportunities and limitations,
• methods for assessing failure probabilities or identifying critical components,
• data groups and taxonomies for component designations and failure categorization.



Learning objectives
In short, the Task 33 has strived at recommending answers to the questions:
• What decision support do operator and other stake holders need?
• What analyses can provide the requested information?
• Which data has to get recorded?
• How to gather and structure the necessary information?