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Exploring wind farm reliability: Key concepts, databases and fault Trees

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  • Hosseini, Seyed Amir
  • Ahmedi, Arsim
  • Blaabjerg, Frede
  • Peyghami, Saeed

Abstract

This review delves into the reliability of wind farms, aiming to identify and assess the reliability of critical components which are essential for their dependable operation. By synthesizing data from various surveys, this study isolates key components crucial to the sustained functionality of wind farms. Each identified component undergoes a thorough assessment using fault tree analysis, providing a detailed evaluation of its impact on the overall reliability of wind energy systems. To achieve this goal, this study explores systematically the failure rates and downtimes of crucial elements within wind farms, such as wind turbines, transformers, HVDC/HVAC systems, and circuit breakers. For an in-depth exploration of transformer failures, numerous surveys from Japan, Brazil, the United Kingdom, and CIGRE have been reviewed. The examination extends to cable systems, encompassing AC and DC configurations in marine and submarine environments, incorporating findings from 59 utility entities across 19 countries. Furthermore, the study scrutinizes circuit breaker failure rates by analyzing data from 27 utilities representing 13 countries. Additionally, to assess the reliability of wind farms, this review introduces a Fault Tree Analysis, categorizing wind farms subsystems and providing insights for reliability allocation and operation and maintenance management. The findings not only shed light on strategies to enhance wind farm reliability but also offer a valuable road map for future research directions and industry best practices.

Suggested Citation

  • Hosseini, Seyed Amir & Ahmedi, Arsim & Blaabjerg, Frede & Peyghami, Saeed, 2025. "Exploring wind farm reliability: Key concepts, databases and fault Trees," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:rensus:v:211:y:2025:i:c:s1364032124009535
    DOI: 10.1016/j.rser.2024.115227
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