Distribution parameter-determining method comparison for airborne wind energy potential assessment in the eastern coastal area of China

Wang, J; Li, Q; Ma, X; Lu, H

Distribution parameter-determining method comparison for airborne wind energy potential assessment in the eastern coastal area of China

Wang, J Li, Q Ma, X Lu, H

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Sustainable Energy Technologies and Assessments, 2022, 52, pp. 102161
Issue Date:: 2022-08-01

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Field	Value	Language
dc.contributor.author	Wang, J
dc.contributor.author	Li, Q
dc.contributor.author	Ma, X
dc.contributor.author	Lu, H https://orcid.org/0000-0001-5655-0237
dc.date.accessioned	2023-03-09T02:25:06Z
dc.date.available	2023-03-09T02:25:06Z
dc.date.issued	2022-08-01
dc.identifier.citation	Sustainable Energy Technologies and Assessments, 2022, 52, pp. 102161
dc.identifier.issn	2213-1388
dc.identifier.uri	http://hdl.handle.net/10453/166754
dc.description.abstract	In recent years, airborne wind energy generation (AWEG) has increasingly been discussed as a better alternative to traditional wind turbine generation owing to less expensive raw materials, higher electricity capacity, and being more friendly to the surrounding environment. Thus, the planning of AWEG-based wind farms is necessary. To control the risk and ensure the future investment revenue to guarantee the ultimate success of this planning, airborne wind energy potential assessment (AWEPA) is essential; however, it has rarely been done so far. In this study, an AWEPA for the eastern coastal area of China was implemented. As wind speed distribution is an essential factor in AWEPA, to guarantee a reliable assessment, selecting a suitable distribution parameter-determining method is critical. In this paper, two conventional numerical parameter-determining methods and three intelligent parameter-determining methods were compared, and the intelligent parameter-determining method embedding the whale optimization algorithm that showed outstanding performance in the comparison was finally selected to be used in the AWEPA. The assessment results show that developing AWEG in the study area is highly likely feasible, and the results also provide some other valuable information for planning.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Sustainable Energy Technologies and Assessments
dc.relation.isbasedon	10.1016/j.seta.2022.102161
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	0905 Civil Engineering, 0906 Electrical and Electronic Engineering
dc.title	Distribution parameter-determining method comparison for airborne wind energy potential assessment in the eastern coastal area of China
dc.type	Journal Article
utslib.citation.volume	52
utslib.for	0905 Civil Engineering
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2024-08-01T00:00:00+1000Z
dc.date.updated	2023-03-09T02:25:02Z
pubs.publication-status	Published
pubs.volume	52

Abstract:

In recent years, airborne wind energy generation (AWEG) has increasingly been discussed as a better alternative to traditional wind turbine generation owing to less expensive raw materials, higher electricity capacity, and being more friendly to the surrounding environment. Thus, the planning of AWEG-based wind farms is necessary. To control the risk and ensure the future investment revenue to guarantee the ultimate success of this planning, airborne wind energy potential assessment (AWEPA) is essential; however, it has rarely been done so far. In this study, an AWEPA for the eastern coastal area of China was implemented. As wind speed distribution is an essential factor in AWEPA, to guarantee a reliable assessment, selecting a suitable distribution parameter-determining method is critical. In this paper, two conventional numerical parameter-determining methods and three intelligent parameter-determining methods were compared, and the intelligent parameter-determining method embedding the whale optimization algorithm that showed outstanding performance in the comparison was finally selected to be used in the AWEPA. The assessment results show that developing AWEG in the study area is highly likely feasible, and the results also provide some other valuable information for planning.

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http://hdl.handle.net/10453/166754