GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities

Concerns on the lack sustainable end-of-life options for wind turbines have significantly increased in recent years. To ensure wind energy continuous growth, this research develops a novel spatiotemporal methodology that sustainably handles end-of-life activities for wind equipment. This research in...

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Main Author: Francisco Haces-Fernandez
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/22/6015
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spelling doaj-d1e938ec2cea4ab78db0d63a0e0db3d82020-11-25T04:10:44ZengMDPI AGEnergies1996-10732020-11-01136015601510.3390/en13226015GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life ActivitiesFrancisco Haces-Fernandez0College of Business Administration, Texas A&M University Kingsville, Kingsville, TX 78363, USAConcerns on the lack sustainable end-of-life options for wind turbines have significantly increased in recent years. To ensure wind energy continuous growth, this research develops a novel spatiotemporal methodology that sustainably handles end-of-life activities for wind equipment. This research introduces the Global Wind Inventory for Future Decommissioning (GoWInD), which assesses and characterizes wind turbines according to individual spatiotemporal decommissioning and sustainability attributes. Applying data from GoWInD, the research developments networks of end-of-life (EoL) centers for wind turbines. The placement and operational levels of EoL centers optimize sustainable decommissioning according to changing spatiotemporal features of wind turbines. The methodology was evaluated for the United States, developing the United States Global Wind Inventory for Future Decommissioning (US—GoWInD), implementing the network of United States end-of-life (US—EoL) centers. Significant imbalances on the temporal and spatial distribution of US wind decommissioning inventory were revealed by the system. Diverse options to effectively handle these imbalances were highlighted by the methodology, including US—EoL center optimization according to placement, operational levels and potential complementarities. Particular attention was paid to components with challenging disposal options. The system can be implemented for diverse geographical locations and alternative spatial and temporal resolutions.https://www.mdpi.com/1996-1073/13/22/6015wind energysustainable end-of-lifewind turbine decommissioningend-of-life centersglobal wind inventory for future decommissioning (GoWInD)
collection DOAJ
language English
format Article
sources DOAJ
author Francisco Haces-Fernandez
spellingShingle Francisco Haces-Fernandez
GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities
Energies
wind energy
sustainable end-of-life
wind turbine decommissioning
end-of-life centers
global wind inventory for future decommissioning (GoWInD)
author_facet Francisco Haces-Fernandez
author_sort Francisco Haces-Fernandez
title GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities
title_short GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities
title_full GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities
title_fullStr GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities
title_full_unstemmed GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities
title_sort gowind: wind energy spatiotemporal assessment and characterization of end-of-life activities
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-11-01
description Concerns on the lack sustainable end-of-life options for wind turbines have significantly increased in recent years. To ensure wind energy continuous growth, this research develops a novel spatiotemporal methodology that sustainably handles end-of-life activities for wind equipment. This research introduces the Global Wind Inventory for Future Decommissioning (GoWInD), which assesses and characterizes wind turbines according to individual spatiotemporal decommissioning and sustainability attributes. Applying data from GoWInD, the research developments networks of end-of-life (EoL) centers for wind turbines. The placement and operational levels of EoL centers optimize sustainable decommissioning according to changing spatiotemporal features of wind turbines. The methodology was evaluated for the United States, developing the United States Global Wind Inventory for Future Decommissioning (US—GoWInD), implementing the network of United States end-of-life (US—EoL) centers. Significant imbalances on the temporal and spatial distribution of US wind decommissioning inventory were revealed by the system. Diverse options to effectively handle these imbalances were highlighted by the methodology, including US—EoL center optimization according to placement, operational levels and potential complementarities. Particular attention was paid to components with challenging disposal options. The system can be implemented for diverse geographical locations and alternative spatial and temporal resolutions.
topic wind energy
sustainable end-of-life
wind turbine decommissioning
end-of-life centers
global wind inventory for future decommissioning (GoWInD)
url https://www.mdpi.com/1996-1073/13/22/6015
work_keys_str_mv AT franciscohacesfernandez gowindwindenergyspatiotemporalassessmentandcharacterizationofendoflifeactivities
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