Early life failure modes and downtime analysis of onshore type-III wind turbines in Turkey

Nur Sarma, Paul Tuohy, Okan Özgönenel, Sinisa Durovic

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Abstract

Operations and maintenance costs, and unplanned downtime accounts for a significant proportion of the total expenditure of windfarms. Therefore, reduction of these costs is essential, which requires a better understanding of the wind turbines' reliability in terms of failure rates and downtime with operational lifetime. Failure rates and downtime are generally logged using condition monitoring systems, which mainly focus on Supervisory Control and Data Acquisition (SCADA) alarm signals. The aim of this paper is to use SCADA alarm statistics to provide a new failure rate and downtime survey and thus to evaluate reliability performance of the major wind turbine components and subsystems. The paper focuses on a modern onshore windfarm located in Turkey with Type-III wind turbines over the course of the first two years of operations, which is the first time reliability data from Turkey has been published in literature.
The presented data can help to provide a better understanding of early life operations, since all maintenance activities, as well as stoppages that caused the wind turbines not to generate electricity were considered in this paper. Furthermore, the evaluation and categorisation of the recorded SCADA alarms, their origins and whether they were associated with planned or unplanned downtime is presented. This analysis shows that early life modern wind turbines have the highest alarm rates and downtime associated with ‘safety’ factors, followed by the ‘electrical systems’, which was found to be the most critical (or unreliable) subsystem. The presented results therefore suggest that early life focus should be on the electrical systems of wind turbines for maximising their operating time and availability. Monthly distributions of both SCADA alarms and downtime rates are also presented to highlight the effects of environmental conditions.
Original languageEnglish
Article number108956
JournalElectric Power Systems Research
Volume216
Early online date6 Dec 2022
DOIs
Publication statusPublished - 1 Mar 2023

Keywords

  • Condition monitoring
  • Downtime
  • Failures
  • Failure mode analysis
  • Reliability
  • SCADA alarms
  • Wind turbine

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