Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS

Muhammet Deveci; Ender Özcan; Robert John; Dragan Pamucar; Himmet Karaman

doi:10.1016/j.asoc.2021.107532

Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS

Muhammet Deveci^*
, Ender Özcan
, Robert John
, Dragan Pamucar
, Himmet Karaman

^*Bu çalışma için yazışmadan sorumlu yazar

Harita Mühendisliği Bölümü

Turkish National Defence University
University of Nottingham
Military Medical Academy

Araştırma sonucu: Dergiye katkı › Makale › bilirkişi

148 Atıf (Scopus)

Özet

Over the past 20 years, the development of offshore wind farms has become increasingly important across the world. One of the most crucial reasons for that is offshore wind turbines have higher average speeds than those onshore, producing more electricity. In this study, a new hybrid approach integrating Interval Rough Numbers (IRNs) into Best-Worst Method (BWM) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) is introduced for multi-criteria intelligent decision support to choose the best offshore wind farm site in a Turkey's coastal area. Four alternatives in the Aegean Sea are considered based on a range of criteria. The results show the viability of the proposed approach which yields Bozcaada as the appropriate site, when compared to and validated using the other multi-criteria decision-making techniques from the literature, including IRN based MABAC, WASPAS, and MAIRCA.

Orijinal dil	İngilizce
Makale numarası	107532
Dergi	Applied Soft Computing
Hacim	109
DOI'lar	https://doi.org/10.1016/j.asoc.2021.107532
Yayın durumu	Yayınlandı - Eyl 2021

Bibliyografik not

Publisher Copyright:
© 2021 Elsevier B.V.

Finansman

This work was supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under the BIDEB-2219 Postdoctoral Research Program grant number 1059B191701014 . The authors also would like to thank Abdulkadir Akpınar from TÜV SÜD Turkey for the useful discussions and feedback about alternatives and ranking.

Finansörler	Finansör numarası
TÜBİTAK
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu	1059B191701014

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 7 Erişilebilir ve Temiz Enerji

Belgeye Erişim

10.1016/j.asoc.2021.107532

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS",

abstract = "Over the past 20 years, the development of offshore wind farms has become increasingly important across the world. One of the most crucial reasons for that is offshore wind turbines have higher average speeds than those onshore, producing more electricity. In this study, a new hybrid approach integrating Interval Rough Numbers (IRNs) into Best-Worst Method (BWM) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) is introduced for multi-criteria intelligent decision support to choose the best offshore wind farm site in a Turkey's coastal area. Four alternatives in the Aegean Sea are considered based on a range of criteria. The results show the viability of the proposed approach which yields Bozcaada as the appropriate site, when compared to and validated using the other multi-criteria decision-making techniques from the literature, including IRN based MABAC, WASPAS, and MAIRCA.",

keywords = "MABAC, MAIRCA, MARCOS, Renewable energy, WASPAS, Wind power",

author = "Muhammet Deveci and Ender {\"O}zcan and Robert John and Dragan Pamucar and Himmet Karaman",

note = "Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",

year = "2021",

month = sep,

doi = "10.1016/j.asoc.2021.107532",

language = "English",

volume = "109",

journal = "Applied Soft Computing",

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TY - JOUR

T1 - Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS

AU - Deveci, Muhammet

AU - Özcan, Ender

AU - John, Robert

AU - Pamucar, Dragan

AU - Karaman, Himmet

PY - 2021/9

Y1 - 2021/9

N2 - Over the past 20 years, the development of offshore wind farms has become increasingly important across the world. One of the most crucial reasons for that is offshore wind turbines have higher average speeds than those onshore, producing more electricity. In this study, a new hybrid approach integrating Interval Rough Numbers (IRNs) into Best-Worst Method (BWM) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) is introduced for multi-criteria intelligent decision support to choose the best offshore wind farm site in a Turkey's coastal area. Four alternatives in the Aegean Sea are considered based on a range of criteria. The results show the viability of the proposed approach which yields Bozcaada as the appropriate site, when compared to and validated using the other multi-criteria decision-making techniques from the literature, including IRN based MABAC, WASPAS, and MAIRCA.

AB - Over the past 20 years, the development of offshore wind farms has become increasingly important across the world. One of the most crucial reasons for that is offshore wind turbines have higher average speeds than those onshore, producing more electricity. In this study, a new hybrid approach integrating Interval Rough Numbers (IRNs) into Best-Worst Method (BWM) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) is introduced for multi-criteria intelligent decision support to choose the best offshore wind farm site in a Turkey's coastal area. Four alternatives in the Aegean Sea are considered based on a range of criteria. The results show the viability of the proposed approach which yields Bozcaada as the appropriate site, when compared to and validated using the other multi-criteria decision-making techniques from the literature, including IRN based MABAC, WASPAS, and MAIRCA.

KW - MABAC

KW - MAIRCA

KW - MARCOS

KW - Renewable energy

KW - WASPAS

KW - Wind power

UR - https://www.scopus.com/pages/publications/85107577684

U2 - 10.1016/j.asoc.2021.107532

DO - 10.1016/j.asoc.2021.107532

M3 - Article

AN - SCOPUS:85107577684

SN - 1568-4946

VL - 109

JO - Applied Soft Computing

JF - Applied Soft Computing

M1 - 107532

ER -

Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS

Özet

Bibliyografik not

Finansman

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap