Prognosis informed stochastic decision making framework for operation and maintenance of wind turbines

Prasanna Tamilselvan, Yibin Wang, Pingfeng Wang, Janet M. Twomey

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

Abstract

Advances in high performance sensing and signal processing technology enable the development of failure prognosis tools for wind turbines to detect, diagnose, and predict the system-wide effects of failure events. Although prognostics can provide valuable information for proactive actions in preventing system failures, the benefits have not been fully utilized for the operation and maintenance decision making of wind turbines. This paper presents a generic failure prognosis informed decision making tool for wind farm operation and maintenance while considering the predictive failure information of individual turbine and its uncertainty. In the presented approach, the probabilistic damage growth model is used to characterize individual wind turbine performance degradation and failure prognostics, whereas the economic loss measured by monetary values and environmental performance measured by unified carbon credits are considered in the decision making process. Based on the customized wind farm information inputs, the developed decision making methodology can be used to identify optimum and robust strategies for wind farm operation and maintenance in order to maximize the economic and environmental benefits concurrently. The efficacy of proposed prognosis informed maintenance strategy is compared with the condition based maintenance strategy and demonstrated with the case study.

Original languageEnglish (US)
Title of host publicationASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages389-396
Number of pages8
ISBN (Print)9780791845110
DOIs
StatePublished - Jan 1 2012
Externally publishedYes
EventASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012 - St. Louis, MO, United States
Duration: Jun 18 2012Jun 20 2012

Publication series

NameASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012

Other

OtherASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012
CountryUnited States
CitySt. Louis, MO
Period6/18/126/20/12

Keywords

  • Economic and environmental impact
  • Predictive maintenance
  • Prognostics
  • Wind farm O&M

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'Prognosis informed stochastic decision making framework for operation and maintenance of wind turbines'. Together they form a unique fingerprint.

  • Cite this

    Tamilselvan, P., Wang, Y., Wang, P., & Twomey, J. M. (2012). Prognosis informed stochastic decision making framework for operation and maintenance of wind turbines. In ASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012 (pp. 389-396). (ASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/ISFA2012-7168