A Physics-based prognostics approach for Tidal Turbines

Fraser Ewing, Philipp R. Thies, Jonathan K. Shek, Claudio Bittencourt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

— Tidal Stream Turbines (TST) have the potential to become an important part of the sustainable energy mix. One of the main hurdles to commercialization is the reliability of the turbine components. Literature from the Offshore Wind sector has shown that the drive train and particularly the Pitch System (PS) are areas of frequent failures and downtime. The Tidal energy sector has much higher device reliability requirements than the wind industry because of the inaccessibility of the turbines. For Tidal energy to become commercially viable it is therefore crucial to make accurate reliability assessments to assist component design choices and to inform maintenance strategy. This paper presents a physics-based prognostics approach for the reliability assessment of Tidal Stream Turbines (TST) during operation. Measured tidal flow data is fed into a turbine hydrodynamic model to generate a synthetic loading regime which is then used in a Physics of Failure model to predict component Remaining Useful Life (RUL). The approach is demonstrated for the failure critical Pitch System (PS) bearing unit of a notional horizontal axis TST. It is anticipated that the approach developed here will enable device/project developers, technical consultants and third party certifiers to undertake robust reliability assessments both during turbine design and operational stages.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538683576
DOIs
Publication statusPublished - Jun 2019
Event2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019 - San Francisco, United States
Duration: 17 Jun 201920 Jun 2019

Publication series

Name2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019

Conference

Conference2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
Country/TerritoryUnited States
CitySan Francisco
Period17/06/1920/06/19

Keywords

  • Fatigue
  • Physics-based Prognostics
  • Reliability
  • RUL
  • Tidal Turbines

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