Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.
Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
David Ferguson (1) F Victoria Catterson (1)
(1) University of Strathclyde, Glasgow, United Kingdom
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Mr Ferguson is a final year PhD student at the Centre for Doctoral Training in Wind Energy at the University of Strathclyde. Prior to his PhD he completed a Master’s degree in Electrical and Electronic Engineering at Heriot Watt University. He is now specialising in wind turbine condition monitoring with a focus in two key areas: reliability of condition monitoring systems and the use of CMS data for failure prediction.
PosterDownload poster (14.71 MB)
Designing for Reliability in Wind Turbine Condition Monitoring Systems
Higher and more favourable wind conditions are the benefits of offshore wind turbines. Associated with offshore wind however is the increased operational and maintenance costs caused by the remoteness of these installations. It is apparent that for offshore wind turbines the use of condition monitoring systems (CMS) can play a key role in reducing the operation and maintenance costs. However for onshore it may not be so obvious. Some researchers have addressed this through the use of models such as discrete-time Markov Chains, Monte Carlo methods and time series modelling in order to quantify the benefits of condition monitoring for onshore wind turbines. Such studies considered the reliability of condition monitoring systems themselves, and found that in order for condition based maintenance to be more cost-effective than periodic maintenance the condition monitoring system must diagnose problems accurately over 80% of the time.
In order to achieve this level of reliability condition monitoring systems must be designed for the harsh environments in which they are to operate. Previous work identified four main categories of robustness which should be considered when designing a wind turbine condition monitoring system. Taking these factors into consideration will result in a more reliable system and reduce the likelihood of issues associated with a poorly designed system. These issues may include: false alarms, undetected faults, inaccurate measurements, or loss of historic fault data.
Through the design, build and installation of two condition monitoring systems in operational Vestas V42 and V47 wind turbines, the authors have taken the lessons learnt in order to provide guidance for the design of new CMS.
Main body of abstract
The aim of the two installed systems was to acquire high frequency data that could be used for algorithm development in order to allow fault diagnostics and prognostics. The systems acquired large volumes (approx. 2TB) of data each month. This data included vibration, voltage and current, temperature and weather parameters.
The first system was operational within the V47 wind turbine for approximately one year. Within this time there were a number of issues with the system. Following the system’s decommissioning it is critiqued under 5 categories of robustness, which are:
• Weather robustness
• Operational robustness
• Manual handling robustness
• Electrical signal robustness
• System software robustness
Under each category the authors identify issues that occurred and what improvements were needed to increase the reliability of the system. These issues included damage from lighting strikes, overheating due to excessive dust intake, and damage to the fibre-optic cable which transfers data from the nacelle to the tower base.
Taking the previous issues into consideration the new system was designed with improvements to minimize the risk of failure due to such issues. Improvements included a revision of the lightning protection, a redesign of the main system enclosure and a revision of the fibre-optic cable routing.
CMS have the potential to significantly reduce the operating costs of wind farms however for this to happen these systems must be able to operate reliably for long periods of time without human intervention. To operate reliably they must be designed and built with consideration for the harsh environment to which they will be subjected. The work presented identifies five key categories which should be considered in order to design a robust CMS.
The aim of this paper is to provide guidance for future designers of wind turbine condition monitoring systems. Lessons learnt from this experience will be used to provide guidance to those designing new condition monitoring systems in order that they can reliably operate within the wind turbine nacelle environment.