Table 1.
Overview of studies on the site selection of offshore wind farms.
| No. | Authors | MCDM Technique | Location | Main findings |
|---|---|---|---|---|
| 1 | Fetanat and Khorasaninejad19 | Fuzzy ANP, fuzzy DEMATEL, and fuzzy ELECTRE | Iran | The optimal site can be chosen from four options, and the method's robustness is proven |
| 2 | Wu et al.27 | ELECTRE-III | China | The developed methodology for OWPS site selection is both valid and practical |
| 3 | Vasileiou et al.56 | AHP | Greece | The finding illustrates the potential for offshore wind and wave energy deployment in Greece, particularly in Crete's offshore areas and a longitudinal zone extending from the north-central to the central Aegean |
| 4 | Chaouachi et al.54 | AHP | Baltic States | The best wind sites are determined by market design, regulatory considerations, and renewable integration targets |
| 5 | Mahdy and Bahaj57 | AHP | Egypt | The established methodology is universal to produce offshore wind suitability map for appropriate offshore wind locations, with three high wind suitable areas around the Red Sea found with the minimum restrictions |
| 6 | Wu et al.58 | Fuzzy AHP | China | The approach is applied to a real-world site selection of offshore wind farms in the Eastern China Sea; it illustrates that maritime safety is a predominant factor |
| 7 | Emeksiz and Demirci59 | AHP | Turkey | Analysis of wind resources and regulations is key to offshore wind farm planning and development at the regional level |
| 8 | Wu et al.28 | Fuzzy ANP-PROMETHEE | China | The decision model proposed is feasible and valid |
| 9 | Abdel-Basset et al.60 | AHP and PROMETHEE-II | Egypt | Rigorous methodological support is presented for site selection to achieve benefits in coastal management |
| 10 | Lo et al.55 | Grey DEMATEL-based ANP | Taiwan | Optimal sites are not only determined by their wind resources and costs; decision-makers must pay particular attention to appropriate strategies and policy planning toward OWPS |