Cargando…

Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach

In response to challenges from the COVID-19 pandemic and climate change to achieve the goal of ensuring sustainable economic growth, offshore wind power development not only provides a clean and sustainable source of energy but also provides opportunities for economic growth and job creation. Offsho...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Chia-Nan, Nguyen, Ngoc-Ai-Thy, Dang, Thanh-Tuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917154/
https://www.ncbi.nlm.nih.gov/pubmed/35277582
http://dx.doi.org/10.1038/s41598-022-08257-2
_version_ 1784668479354306560
author Wang, Chia-Nan
Nguyen, Ngoc-Ai-Thy
Dang, Thanh-Tuan
author_facet Wang, Chia-Nan
Nguyen, Ngoc-Ai-Thy
Dang, Thanh-Tuan
author_sort Wang, Chia-Nan
collection PubMed
description In response to challenges from the COVID-19 pandemic and climate change to achieve the goal of ensuring sustainable economic growth, offshore wind power development not only provides a clean and sustainable source of energy but also provides opportunities for economic growth and job creation. Offshore wind energy projects have been promptly suggested in Vietnam due to policy advancement, with the country's excellent wind resources. The success of an offshore wind energy project is decided mainly by choosing the best location for offshore wind power station (OWPS) construction, which is a complex multicriteria decision-making (MCDM) problem with the coexistence of conflicting factors. There is a problem with incomplete decision information use and information loss during the decision-making process, and it is easy to overlook the interaction difficulty in a fuzzy environment. To address the complex nature of the prioritization problem posed, this study proposes a hybrid MCDM framework combining the spherical fuzzy analytical hierarchy process (SF-AHP) and weighted aggregated sum product assessment (WASPAS). SF-AHP is used in the first stage to determine the significance levels of OWPS evaluation criteria. WASPAS is then utilized to rank locations of OWPS. A comprehensive set of evaluation criteria developed based on the concept of sustainable development has been recognized by reviewing the literature review and interviewing experts to practice the two-stage MCDM model. A real case study for Vietnam is conducted to test the effectiveness of the proposed method. The best location schemes have been determined by using the decision framework. The results of the sensitivity analysis and a comparison analysis demonstrate that the decision framework is practical and robust. The proposed methodology can be used to attain a decision-making process at the regional level for offshore wind farm planning and coastal development, and the study results encourage the establishment of renewable energy development policies.
format Online
Article
Text
id pubmed-8917154
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-89171542022-03-14 Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach Wang, Chia-Nan Nguyen, Ngoc-Ai-Thy Dang, Thanh-Tuan Sci Rep Article In response to challenges from the COVID-19 pandemic and climate change to achieve the goal of ensuring sustainable economic growth, offshore wind power development not only provides a clean and sustainable source of energy but also provides opportunities for economic growth and job creation. Offshore wind energy projects have been promptly suggested in Vietnam due to policy advancement, with the country's excellent wind resources. The success of an offshore wind energy project is decided mainly by choosing the best location for offshore wind power station (OWPS) construction, which is a complex multicriteria decision-making (MCDM) problem with the coexistence of conflicting factors. There is a problem with incomplete decision information use and information loss during the decision-making process, and it is easy to overlook the interaction difficulty in a fuzzy environment. To address the complex nature of the prioritization problem posed, this study proposes a hybrid MCDM framework combining the spherical fuzzy analytical hierarchy process (SF-AHP) and weighted aggregated sum product assessment (WASPAS). SF-AHP is used in the first stage to determine the significance levels of OWPS evaluation criteria. WASPAS is then utilized to rank locations of OWPS. A comprehensive set of evaluation criteria developed based on the concept of sustainable development has been recognized by reviewing the literature review and interviewing experts to practice the two-stage MCDM model. A real case study for Vietnam is conducted to test the effectiveness of the proposed method. The best location schemes have been determined by using the decision framework. The results of the sensitivity analysis and a comparison analysis demonstrate that the decision framework is practical and robust. The proposed methodology can be used to attain a decision-making process at the regional level for offshore wind farm planning and coastal development, and the study results encourage the establishment of renewable energy development policies. Nature Publishing Group UK 2022-03-11 /pmc/articles/PMC8917154/ /pubmed/35277582 http://dx.doi.org/10.1038/s41598-022-08257-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Chia-Nan
Nguyen, Ngoc-Ai-Thy
Dang, Thanh-Tuan
Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach
title Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach
title_full Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach
title_fullStr Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach
title_full_unstemmed Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach
title_short Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach
title_sort offshore wind power station (owps) site selection using a two-stage mcdm-based spherical fuzzy set approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917154/
https://www.ncbi.nlm.nih.gov/pubmed/35277582
http://dx.doi.org/10.1038/s41598-022-08257-2
work_keys_str_mv AT wangchianan offshorewindpowerstationowpssiteselectionusingatwostagemcdmbasedsphericalfuzzysetapproach
AT nguyenngocaithy offshorewindpowerstationowpssiteselectionusingatwostagemcdmbasedsphericalfuzzysetapproach
AT dangthanhtuan offshorewindpowerstationowpssiteselectionusingatwostagemcdmbasedsphericalfuzzysetapproach