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.
| Original language | English |
|---|---|
| Article number | 107532 |
| Journal | Applied Soft Computing |
| Volume | 109 |
| DOIs | |
| Publication status | Published - Sept 2021 |
Bibliographical note
Publisher Copyright:© 2021 Elsevier B.V.
Funding
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.
| Funders | Funder number |
|---|---|
| TÜBİTAK | |
| Türkiye Bilimsel ve Teknolojik Araştirma Kurumu | 1059B191701014 |
Keywords
- MABAC
- MAIRCA
- MARCOS
- Renewable energy
- WASPAS
- Wind power
