Analyzing a Decade of Wind Turbine Accident News with Topic Modeling

Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is scarce. The research presen...

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Autores principales:	Gürdal Ertek, Lakshmi Kailas
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	wind energy wind turbine accidents accident analysis topic modeling association mining data analytics Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/8a0c0e74ba6b4329836f8e25c17f9e65
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spelling	oai:doaj.org-article:8a0c0e74ba6b4329836f8e25c17f9e652021-11-25T19:04:07ZAnalyzing a Decade of Wind Turbine Accident News with Topic Modeling10.3390/su1322127572071-1050https://doaj.org/article/8a0c0e74ba6b4329836f8e25c17f9e652021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12757https://doaj.org/toc/2071-1050Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is scarce. The research presented here, upon construction of a text corpus of 721 selected wind turbine accident and failure news reports, develops and applies a custom-developed data analytics framework that integrates tabular analysis, visualization, text mining, and machine learning. Topic modeling was applied for the first time to identify and classify recurring themes in wind turbine accident news, and association mining was applied to identify contextual terms associated with death and injury. The tabular and visual analyses relate accidents to location (offshore vs. onshore), wind turbine life cycle phases (transportation, construction, operation, and maintenance), and the incidence of death and injury. As one of the insights, more incidents were found to occur during operation and transportation. Through topic modeling, topics associated most with deaths and injuries were revealed. The results could benefit wind turbine manufacturers, service providers, energy companies, insurance companies, government bodies, non-profit organizations, researchers, and other stakeholders in the wind energy sector.Gürdal ErtekLakshmi KailasMDPI AGarticlewind energywind turbine accidentsaccident analysistopic modelingassociation miningdata analyticsEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12757, p 12757 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	wind energy wind turbine accidents accident analysis topic modeling association mining data analytics Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	wind energy wind turbine accidents accident analysis topic modeling association mining data analytics Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Gürdal Ertek Lakshmi Kailas Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
description	Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is scarce. The research presented here, upon construction of a text corpus of 721 selected wind turbine accident and failure news reports, develops and applies a custom-developed data analytics framework that integrates tabular analysis, visualization, text mining, and machine learning. Topic modeling was applied for the first time to identify and classify recurring themes in wind turbine accident news, and association mining was applied to identify contextual terms associated with death and injury. The tabular and visual analyses relate accidents to location (offshore vs. onshore), wind turbine life cycle phases (transportation, construction, operation, and maintenance), and the incidence of death and injury. As one of the insights, more incidents were found to occur during operation and transportation. Through topic modeling, topics associated most with deaths and injuries were revealed. The results could benefit wind turbine manufacturers, service providers, energy companies, insurance companies, government bodies, non-profit organizations, researchers, and other stakeholders in the wind energy sector.
format	article
author	Gürdal Ertek Lakshmi Kailas
author_facet	Gürdal Ertek Lakshmi Kailas
author_sort	Gürdal Ertek
title	Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
title_short	Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
title_full	Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
title_fullStr	Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
title_full_unstemmed	Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
title_sort	analyzing a decade of wind turbine accident news with topic modeling
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/8a0c0e74ba6b4329836f8e25c17f9e65
work_keys_str_mv	AT gurdalertek analyzingadecadeofwindturbineaccidentnewswithtopicmodeling AT lakshmikailas analyzingadecadeofwindturbineaccidentnewswithtopicmodeling
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Analyzing a Decade of Wind Turbine Accident News with Topic Modeling

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