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

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. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

The development of offshore wind farms has become increasingly important over the past 20 years due to higher average wind speeds at sea. A new hybrid approach integrating Interval Rough Numbers into Best-Worst Method and Measurement of Alternatives and Ranking according to Compromise Solution was introduced in this study for intelligent decision support in choosing the best offshore wind farm site. The results demonstrated the feasibility of the proposed approach and identified Bozcaada as the most suitable site.