Wind Turbine Accidents: A Data Mining Study

Sobhan Asian, Gürdal Ertek, Cagri Haksoz, Sena Pakter, Soner Ulun

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)

Abstract

While the global production of wind energy is increasing, there exists a significant gap in the academic and practice literature regarding the analysis of wind turbine accidents. This paper presents the results obtained from the analysis of 240 wind turbine accidents from around the world. The main focus of this paper is revealing the associations between several factors and deaths and injuries in wind turbine accidents. Specifically, the associations of death and injuries with the stage of the wind turbine's life cycle (transportation, construction, operation, and maintenance) and the main cause factor categories (human, system/equipment, and nature) were studied. To this end, we conducted a detailed investigation that integrates exploratory and statistical data analysis and data mining methods. This paper presents a multitude of insights regarding the accidents and discusses implications for wind turbine manufacturers, engineering and insurance companies, and government organizations.

Original languageEnglish
Article number7489036
Pages (from-to)1567-1578
Number of pages12
JournalIEEE Systems Journal
Volume11
Issue number3
DOIs
Publication statusPublished - Sep 2017
Externally publishedYes

Keywords

  • Accidents
  • data analysis
  • data mining
  • wind energy
  • wind power generation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Wind Turbine Accidents: A Data Mining Study'. Together they form a unique fingerprint.

Cite this