A literature review: Wind energy within the scope of MCDM methods

Abstract

Renewable energy sources (RES) are vital for environmental sustainability. With the depletion and damage of fossil fuels to nature, energy production from clean and inexhaustible RES has become widespread. Wind energy, one of the RES, is a clean energy source that does not emit any harmful waste to the environment. Wind energy is a low-cost energy source that is mostly used for electricity generation. Criteria such as wind speed, turbine structure and the characteristics of the areas where the wind turbines will be located are effective on the amount of energy to be produced. In this study, a comprehensive review of the studies using MCDM methods related to wind energy is made. In the manner of the statistical data obtained from the 97 studies examined, it has been observed that the wind energy investments and the scientific publications made in these countries do not progress linearly with each other. The fact that countries have different wind energy potentials and the difference in the countries' interest in RES is thought to be effective in this regard. While there are articles in the literature in which studies on RES are discussed together with MCDM methods, there is no comprehensive review study in which wind energy and MCDM methods are discussed together. According to our best knowledge, this is the first study to comprehensively evaluate wind energy studies in terms of MCDM methods. With this study, a framework has been presented for subsequent studies on the application of MCDM methods in wind energy.

Keywords

• Renewable energy
• Wind energy
• MCDM
• Clean energy

References

1. [1] Rybár, R., Kudelas, D. and Beer, M., “Selected problems of classification of energy sources-What are renewable energy sources?”, Acta Montanistica Slovaca, 20: 3, (2015).
2. [2] O’riordan T., “Environmental science for environmental management”, Pearson Education Limited, London, (1999).
3. [3] Dudley B., 2016. BP statistical review of world energy 2016. https://www.bp.com/content /dam/bp/business-sites/en/global/corporate/pdfs/news-and insights/speeches/bp-statistical-review-of-world-energy-2016-bob-dudley-speech.pdf. Access date: 29.06.2022.
4. [4] https://www.iea.org/reports/global-energy-review-2021. Access date: 09.03.2022.
5. [5] Eroğlu, Ö., “Multi-Criteria Decision Support System for Selection of Renewable Energy Resources within the Scope of the Energy Needs of the Base Region”, Ph.D.Thesis, Graduate School of Natural and Applied Sciences, Gazi University, 5-7, 2021.
6. [6] Cui, X., Sun, H., Dong, Z., Liu, Z., Li, C., Zhang, Z and Li, L., “Temporal variation of the wind environment and its possible causes in the Mu Us Dunefield of Northern China, 1960–2014”. Theoretical and Applied Climatology, 135(3): 1017-1029, (2019).
7. [7] Bailey, B. H., McDonald, S. L., Bernadett, D. W., Markus, M. J. and Elsholz, K. V., “Wind resource assessment handbook: Fundamentals for conducting a successful monitoring program (No. NREL/SR-440-22223; ON: DE97000250)” National Renewable Energy Lab., Golden, Co. (US); AWS Scientific, Inc., Albany, NY (US), (1997).
8. [8] https://www.energy.gov/eere/wind/advantages-and-challenges-wind-energy. Access date: 24.01.2022.

9. [9] https://gwec.net/global-wind-report-2021/. Access date: 24.01.2022.
10. [10] Perveen, R., Kishor, N. and Mohanty, S. R., “Off-shore wind farm development: Present status and challenges”, Renewable and Sustainable Energy Reviews, 29: 780-792, (2014).
11. [11] Aras, H., Erdoğmuş, Ş. and Koç, E., “Multi-criteria selection for a wind observation station location using analytic hierarchy process”, Renewable Energy, 29(8): 1383-1392, (2004).
12. [12] Tegou, L. I., Polatidis, H. and Haralambopoulos, D. A. “Environmental management framework for wind farm siting: Methodology and case study”, Journal of Environmental Management, 91(11): 2134-2147, (2010).
13. [13] Höfer, T., Sunak, Y., Siddique, H. and Madlener, R., “Wind farm siting using a spatial Analytic Hierarchy Process approach: A case study of the Städteregion Aachen”, Applied Energy, 163: 222-243, (2016).
14. [14] Villacreses, G., Gaona, G., Martínez-Gómez, J. and Jijón, D. J., “Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador”, Renewable Energy, 109: 275-286, (2017).
15. [15] Lozano-Minguez, E., Kolios, A. J. and Brennan, F. P., “Multi-criteria assessment of offshore wind turbine support structures”, Renewable Energy,36(11): 2831-2837, (2011).
16. [16] Wu, Y., Zhang, J., Yuan, J., Geng, S. and Zhang, H., “Study of decision framework of offshore wind power station site selection based on ELECTRE-III under intuitionistic fuzzy environment: A case of China”, Energy Conversion and Management, 113: 66-81, (2016).
17. [17] Al-Yahyai, S., Charabi, Y., Gastli, A. and Al-Badi, A., “Wind farm land suitability indexing using multi-criteria analysis”, Renewable Energy, 44: 80-87, (2012).
18. [18] Sánchez-Lozano, J. M., García-Cascales, M. S. and Lamata, M. T., “GIS-based onshore wind farm site selection using Fuzzy Multi-Criteria Decision Making methods. Evaluating the case of Southeastern Spain”, Applied Energy, 171: 86-102, (2016).
19. [19] Fetanat, A. and Khorasaninejad, E., “A novel hybrid MCDM approach for offshore wind farm site selection: A case study of Iran”, Ocean & Coastal Management, 109: 17-28, (2015).
20. [20] Onar, S. C., Oztaysi, B., Otay, İ. and Kahraman, C., “Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets”, Energy, 90: 274-285, (2015).
21. [21] Ayodele, T. R., Ogunjuyigbe, A. S. O., Odigie, O. and Munda, J. L., “A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria”, Applied Energy, 228: 1853-1869, (2018).
22. [22] Vasileiou, M., Loukogeorgaki, E. and Vagiona, D. G., “GIS-based multi-criteria decision analysis for site selection of hybrid offshore wind and wave energy systems in Greece”, Renewable and Sustainable Energy Reviews, 73: 745-757, (2017).
23. [23] Baseer, M. A., Rehman, S., Meyer, J. P. and Alam, M. M., “GIS-based site suitability analysis for wind farm development in Saudi Arabia”, Energy, 141: 1166-1176, (2017).
24. [24] Ali, S., Taweekun, J., Techato, K., Waewsak, J. and Gyawali, S., “GIS based site suitability assessment for wind and solar farms in Songkhla, Thailand”, Renewable Energy, 132: 1360-1372, (2019).
25. [25] Mahdy, M. and Bahaj, A. S., “Multi criteria decision analysis for offshore wind energy potential in Egypt”, Renewable energy, 118: 278-289, (2018).
26. [26] Bagočius, V., Zavadskas, E. K. and Turskis, Z., “Multi-person selection of the best wind turbine based on the multi-criteria integrated additive-multiplicative utility function”, Journal of Civil Engineering and Management, 20(4): 590-599, (2014).
27. [27] Lee, A. H., Hung, M. C., Kang, H. Y. and Pearn, W. L., “A wind turbine evaluation model under a multi-criteria decision making environment”, Energy Conversion and Management, 64: 289-300, (2012).
28. [28] Chaouachi, A., Covrig, C. F. and Ardelean, M., “Multi-criteria selection of offshore wind farms: Case study for the Baltic States”, Energy Policy, 103: 179-192, (2017).
29. [29] Ziemba, P., Wątróbski, J., Zioło, M. and Karczmarczyk, A., “Using the PROSA method in offshore wind farm location problems”, Energies, 10(11): 1755, (2017).
30. [30] Qiu, D., Dinçer, H., Yüksel, S. and Ubay, G. G., “Multi-faceted analysis of systematic risk-based wind energy investment decisions in E7 economies using modified hybrid modeling with IT2 fuzzy sets”, Energies, 13(6): 1423, (2020).
31. [31] Kang, H. Y., Hung, M. C., Pearn, W. L., Lee, A. H. and Kang, M. S., “An integrated multi-criteria decision making model for evaluating wind farm performance”, Energies, 4(11): 2002-2026, (2011).
32. [32] Gumus, S., Kucukvar, M. and Tatari, O., “Intuitionistic fuzzy multi-criteria decision making framework based on life cycle environmental, economic and social impacts: The case of US wind energy”, Sustainable Production and Consumption, 8: 78-92, (2016).
33. [33] Vagiona, D. G. and Karanikolas, N. M., “A multicriteria approach to evaluate offshore wind farms siting in Greece”, Global NEST Journal, 14(2): 235-243, (2012).
34. [34] Abdel-Basset, M., Gamal, A., Chakrabortty, R. K. and Ryan, M., “A new hybrid multi-criteria decision-making approach for location selection of sustainable offshore wind energy stations: A case study”, Journal of Cleaner Production, 280: 124462, (2021).
35. [35] Chatterjee, N. and Bose, G., “A COPRAS-F base multi-criteria group decision making approach for site selection of wind farm”, Decision Science Letters, 2(1): 1-10, (2013).
36. [36] Dinmohammadi, A. and Shafiee, M., “Determination of the most suitable technology transfer strategy for wind turbines using an integrated AHP-TOPSIS decision model”, Energies, 10(5): 642, (2017).
37. [37] Dhiman, H. S. and Deb, D., “Fuzzy TOPSIS and fuzzy COPRAS based multi-criteria decision making for hybrid wind farms”, Energy, 202: 117755, (2020).
38. [38] De la Fuente, A., Armengou, J., Pons, O. and Aguado, A., “Multi-criteria decision-making model for assessing the sustainability index of wind-turbine support systems: application to a new precast concrete alternative”, Journal of Civil Engineering and Management, 23(2): 194-203, (2017).
39. [39] Deveci, M., Cali, U., Kucuksari, S. and Erdogan, N., “Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland”, Energy, 198: 117317, (2020).
40. [40] Zhou, S. and Yang, P., “Risk management in distributed wind energy implementing Analytic Hierarchy Process”, Renewable Energy, 150: 616-623, (2020).
41. [41] Moradi, S., Yousefi, H., Noorollahi, Y. and Rosso, D., “Multi-criteria decision support system for wind farm site selection and sensitivity analysis: Case study of Alborz Province, Iran”, Energy Strategy Reviews, 29: 100478, (2020).
42. [42] Kolios, A. J., Rodriguez-Tsouroukdissian, A. and Salonitis, K., “Multi-criteria decision analysis of offshore wind turbines support structures under stochastic inputs”, Ships and Offshore Structures, 11(1): 38-49, (2016).
43. [43] Sagbansua, L. and Balo, F., “Decision making model development in increasing wind farm energy efficiency”, Renewable Energy, 109: 354-362, (2017).
44. [44] Rehman, S. and Khan, S. A., “Fuzzy logic based multi-criteria wind turbine selection strategy—A case study of Qassim, Saudi Arabia”, Energies, 9(11): 872, (2016).
45. [45] Kolios, A., Collu, M., Chahardehi, A., Brennan, F. P. and Patel, M. H., “A multi-criteria decision making method to compare support structures for offshore wind turbines”, In European Wind Energy Conference, Warsaw, (2010).
46. [46] Koc, A., Turk, S. and Şahin, G., “Multi-criteria of wind-solar site selection problem using a GIS-AHP-based approach with an application in Igdır Province/Turkey”, Environmental Science and Pollution Research, 26(31): 32298-32310, (2019).
47. [47] Xu, Y., Li, Y., Zheng, L., Cui, L., Li, S., Li, W. and Cai, Y., “Site selection of wind farms using GIS and multi-criteria decision making method in Wafangdian, China”, Energy, 207: 118222, (2020).
48. [48] Shirgholami, Z., Zangeneh, S. N. and Bortolini, M., “Decision system to support the practitioners in the wind farm design: A case study for Iran mainland”, Sustainable Energy Technologies and Assessments, 16: 1-10, (2016).
49. [49] Okokpujie, I. P., Okonkwo, U. C., Bolu, C. A., Ohunakin, O. S., Agboola, M. G. and Atayero, A. A., “Implementation of multi-criteria decision method for selection of suitable material for development of horizontal wind turbine blade for sustainable energy generation”, Heliyon, 6(1): e03142, (2020).
50. [50] Mostafaeipour, A., Dehshiri, S. J. H., Dehshiri, S. S. H. and Jahangiri, M., “Prioritization of potential locations for harnessing wind energy to produce hydrogen in Afghanistan”, International Journal of Hydrogen Energy, 45(58): 33169-33184, (2020).
51. [51] Al-Shabeeb, A. R., Al-Adamat, R. and Mashagbah, A., “AHP with GIS for a preliminary site selection of wind turbines in the North West of Jordan”, International Journal of Geosciences, 7(10): 1208, (2016).
52. [52] Değirmenci, S., Bingöl, F. and Sofuoglu, S. C., “MCDM analysis of wind energy in Turkey: decision making based on environmental impact”, Environmental Science and Pollution Research, 25(20): 19753-19766, (2018).
53. [53] Rezaian, S. and Jozi, S. A., “Application of multi criteria decision-making technique in site selection of wind farm-a case study of Northwestern Iran”, Journal of the Indian Society of Remote Sensing, 44(5): 803-809, (2016).
54. [54] Mostafaeipour, A., Rezaei, M., Jahangiri, M. and Qolipour, M., “Feasibility analysis of a new tree-shaped wind turbine for urban application: A case study”, Energy & Environment, 31(7): 1230-1256, (2020).
55. [55] Mytilinou, V., Lozano-Minguez, E. and Kolios, A., “A framework for the selection of optimum offshore wind farm locations for deployment”, Energies, 11(7): 1855, (2018).
56. [56] Díaz-Cuevas, P., Biberacher, M., Domínguez-Bravo, J. and Schardinger, I., “Developing a wind energy potential map on a regional scale using GIS and multi-criteria decision methods: the case of Cadiz (south of Spain)”, Clean Technologies and Environmental Policy, 20(6): 1167-1183, (2018).
57. [57] Dhiman, H. S., Deb, D., Muresan, V. and Unguresan, M. L., “Multi-criteria decision making approach for hybrid operation of wind farms”, Symmetry, 11(5): 675, (2019).
58. [58] Caporale, D., Sangiorgio, V., Amodio, A. and De Lucia, C., “Multi-criteria and focus group analysis for social acceptance of wind energy”, Energy Policy, 140: 111387, (2020).
59. [59] Almutairi, K., Dehshiri, S. S. H., Dehshiri, S. J. H., Mostafaeipour, A., Issakhov, A. and Techato, K., “A thorough investigation for development of hydrogen projects from wind energy: A case study”, International Journal of Hydrogen Energy, 46(36): 18795-18815, (2021).
60. [60] Hwang, G. H., Wei, L. S., Ching, K. B. and Lin, N. S., “Wind farm allocation in Malaysia based on multi-criteria decision making method”, National Postgraduate Conference (pp. 1-6). IEEE, (2011).
61. [61] Supçiller, A. A. and Toprak, F., “Selection of wind turbines with multi-criteria decision making techniques involving neutrosophic numbers: A case from Turkey”, Energy, 207: 118237, (2020).
62. [62] Şağbanşua, L. and Balo, F., “Multi-criteria decision making for 1.5 MW wind turbine selection”, Procedia Computer Science, 111: 413-419, (2017).
63. [63] Govindan, K. and Shankar, M., “Evaluating the essential barrier to off-shore wind energy–an Indian perspective” International Journal of Energy Sector Management, (2016).
64. [64] Tercan, E., Tapkın, S., Latinopoulos, D., Dereli, M. A., Tsiropoulos, A. and Ak, M. F., “A GIS-based multi-criteria model for offshore wind energy power plants site selection in both sides of the Aegean Sea”, Environmental Monitoring and Assessment, 192(10): 1-20, (2020).
65. [65] Rehman, A. U., Abidi, M. H., Umer, U. and Usmani, Y. S., “Multi-criteria decision-making approach for selecting wind energy power plant locations”, Sustainability, 11(21): 6112, (2019).
66. [66] Wang, C. N., Yang, C. Y. and Cheng, H. C., “Fuzzy multi-criteria decision-making model for supplier evaluation and selection in a wind power plant project”, Mathematics, 7(5): 417, (2019).
67. [67] Khan, S. A. and Rehman, S., “On the use of unified and-or fuzzy aggregation operator for multi-criteria decision making in wind farm design process using wind turbines in 500 kW–750 kW range”, IEEE International Conference on Fuzzy Systems, 1-6, (2012).
68. [68] Deveci, M., Özcan, E., John, R., Pamucar, D. and Karaman, H., “Offshore wind farm site selection using interval rough numbers based Best Worst Method and MARCOS”, Applied Soft Computing, 107532, (2021).
69. [69] Sagbas, A. and Mazmanoglu, A., “Use of multicriteria decision analysis to assess alternative wind power plants”, Journal of Engineering Research, 2(1), (2014).
70. [70] Li, M., Xu, Y., Guo, J., Li, Y. and Li, W., “Application of a GIS-Based Fuzzy Multi-Criteria Evaluation Approach for Wind Farm Site Selection in China”, Energies, 13(10): 2426, (2020).
71. [71] Deveci, M., Özcan, E. and John, R., “Offshore wind farms: A fuzzy approach to site selection in a black sea region”, IEEE Texas Power and Energy Conference (TPEC), 1-6, (2020).
72. [72] Łaska, G, “Wind energy and multi-criteria analysis in making decisions on the location of wind farms”, Procedia Engineering, 182: 418-424, (2017).
73. [73] Rehman, S. and Khan, S. A., “Goal Programming-Based Two-Tier Multi-Criteria Decision-Making Approach for Wind Turbine Selection”, Applied Artificial Intelligence, 33(1): 27-53, (2019).
74. [74] Arı, E. S. and Gencer, C., “The use and comparison of a deterministic, a stochastic, and a hybrid multiple-criteria decision-making method for site selection of wind power plants: An application in Turkey”. Wind Engineering, 44(1): 60-74, (2020).
75. [75] Ziemba, P., “Multi-criteria fuzzy evaluation of the planned offshore wind farm investments in Poland”, Energies, 14(4): 978, (2021).
76. [76] Heidarzade, F., Varzandeh, M. H. M., Rahbari, O., Zavadskas, E. K. and Vafaeipour, M., “Placement of wind farms based on a hybrid multi criteria decision making for Iran”, Proceedings of the 4th World Sustainability Forum, 4: 1-20, (2014).
77. [77] Lo, H. W., Hsu, C. C., Chen, B. C. and Liou, J. J., “Building a grey-based multi-criteria decision-making model for offshore wind farm site selection”, Sustainable Energy Technologies and Assessments, 43: 100935, (2021).
78. [78] Wu, J., Wang, H., Wang, W. and Zhang, Q., “Performance evaluation for sustainability of wind energy project using improved multi-criteria decision-making method”, Journal of Modern Power Systems and Clean Energy, 7(5): 1165-1176, (2019).
79. [79] Rehman, S., Khan, S. A. and Alhems, L. M., “Application of TOPSIS Approach to Multi-Criteria Selection of Wind Turbines for On-Shore Sites”, Applied Sciences, 10(21): 7595, (2020).
80. [80] Almutairi, K., Dehshiri, S. S. H., Dehshiri, S. J. H., Mostafaeipour, A., Jahangiri, M. and Techato, K., “Technical, economic, carbon footprint assessment, and prioritizing stations for hydrogen production using wind energy: A case study”, Energy Strategy Reviews, 36: 100684, (2021).
81. [81] Richmond, M., Balaam, T., Causon, P., Cevasco, D., Leimeister, M., Kolios, A. and Brennan, F., “Multi-criteria decision analysis for benchmarking human-free lifting solutions in the offshore wind energy environment”, Energies, 11(5): 1175, (2018).
82. [82] Ali, S. and Jang, C. M., “Selection of Best-suited wind turbines for new wind farm sites using techno-economic and GIS analysis in South Korea”, Energies, 12(16): 3140, (2019).
83. [83] Amjad, F., Agyekum, E. B., Shah, L. A. and Abbas, A., “Site location and allocation decision for onshore wind farms, using spatial multi-criteria analysis and density-based clustering. A techno-economic-environmental assessment, Ghana”, Sustainable Energy Technologies and Assessments, 47, 101503, (2021).
84. [84] Li, Z., “Study of site suitability assessment of regional wind resources development based on multi-criteria decision”, Clean Technologies and Environmental Policy, 20(6): 1147-1166, (2018).
85. [85] Elmahmoudi, F., Abra, O. E., Raihani, A., Serrar, O. and Bahatti, L., “GIS Based Fuzzy Analytic Hierarchy Process for wind Energy Sites Selection”, International Conference on Advanced Communication Technologies and Networking (CommNet), 1-8, (2019).
86. [86] Rehman, S., Khan, S. A. and Alhems, L. M., “A Rule-Based Fuzzy Logic Methodology for Multi-Criteria Selection of Wind Turbines. Sustainability” 12(20): 8467, (2020).
87. [87] Wang, C. N. and Dang, T. T., “Location optimization of wind plants using DEA and fuzzy multi-criteria decision making: A case study in Vietnam”, IEEE Access, 9: 116265-116285, (2021).
88. [88] Afsordegan, A., Sánchez, M., Agell, N., Aguado, J. C. and Gamboa, G., “A comparison of two MCDM methodologies in the selection of a windfarm location in Catalonia”, In CCIA, 227-236, (2014).
89. [89] Elmahmoudi, F., Abra, O. E. K., Raihani, A., Serrar, O. and Bahatti, L., “Elaboration of a Wind Energy Potential Map in Morocco using GIS and Analytic Hierarchy Process”, Engineering, Technology & Applied Science Research, 10(4): 6068-6075, (2020).
90. [90] Bertsiou, M. M., Theochari, A. P. and Baltas, E., “Multi‐criteria analysis and Geographic Information Systems methods for wind turbine siting in a North Aegean Island”, Energy Science & Engineering, 9(1): 4-18, (2021).
91. [91] Genç, M. S., Karipoğlu, F., Koca, K. and Azgın, Ş. T., “Suitable site selection for offshore wind farms in Turkey’s seas: GIS-MCDM based approach”, Earth Science Informatics, 1-13, (2021).
92. [92] Eroğlu, H., “Multi-criteria decision analysis for wind power plant location selection based on fuzzy AHP and geographic information systems”, Environment, Development and Sustainability, 1-33, (2021).
93. [93] Elgabiri, M., Palmer, D., Al Buflasa, H. and Thomson, M., “Offshore wind energy potential for Bahrain via multi-criteria evaluation”, Wind Engineering, 0309524X20925399, (2020).
94. [94] Aryanfar, A., Gholami, A., Pourgholi, M., Zandi, M. and Khosravi, A., “Using type-2 fuzzy in decision-making for wind potential assessment in Iran”, 7th Iran Wind Energy Conference (IWEC2021), 1-5, IEEE, (2021).
95. [95] Liu, L., Zhou, J., Dong, H., Tao, Y., Wu, Y. and Wang, Y., “Investment Risk Assessment of Dispersed Wind Power in Low Wind Speed Area Using a Hybrid Multi-Criteria Decision-Making Approach Based on Hesitant Fuzzy Linguistic Environment”, Mathematical Problems in Engineering, (2020).
96. [96] Supçiller, A. A. and Bayramoğlu, S., “Wind farm location selection with interval grey numbers based I-GRA and grey EDAS methods”, Journal of the Faculty of Engineering and Architecture of Gazi University, 35(4): 1847-1860, (2020).
97. [97] Uzunlar, F. B., Güler, Ö. and Kalenderli, Ö., “Wind Turbine Selection Method by Using Analytical Network Process Associated With Cost Benefit Analysis”, Environmental Engineering & Management Journal, 19(5), (2020).
98. [98] Vinhoza, A. and Schaeffer, R., “Brazil's offshore wind energy potential assessment based on a Spatial Multi-Criteria Decision Analysis”, Renewable and Sustainable Energy Reviews, 146, 111185, (2021).
99. [99] Gil-García, I. C., Ramos-Escudero, A., García-Cascales, M. S., Dagher, H. and Molina-García, A., “Fuzzy GIS-based MCDM solution for the optimal offshore wind site selection: The Gulf of Maine case”, Renewable Energy, 183: 130-147, (2022).
100. [100] Ma, Y., Xu, L., Cai, J., Cao, J., Zhao, F. and Zhang, J., “A novel hybrid multi-Criteria decision-Making approach for offshore wind turbine selection”, Wind Engineering, 45(5): 1273-1295, (2021).
101. [101] Asadi, M. and Pourhossein, K., “Wind farm site selection considering turbulence intensity”, Energy, 236, 121480, (2021).
102. [102] Elhosiny, A. M., El-Ghareeb, H., Shabana, B. T. and Abouelfetouh, A., “A Hybrid Neutrosophic GIS-MCDM Method Using a Weighted Combination Approach for Selecting Wind Energy Power Plant Locations: A Case Study of Sinai Peninsula, Egypt”, International Journal of Fuzzy Logic and Intelligent Systems, 21(1): 12-28, (2021).
103. [103] Gkeka-Serpetsidaki, P. and Tsoutsos, T., “A methodological framework for optimal siting of offshore wind farms: A case study on the Island of Crete”, Energy, 239, 122296, (2022).
104. [104] Kabak, M. and Akalın, S., “A model proposal for selecting the installation location of offshore wind energy turbines”, International Journal of Energy and Environmental Engineering, 1-14, (2021).
105. [105] Narayanamoorthy, S., Ramya, L., Kang, D., Baleanu, D., Kureethara, J. V. and Annapoorani, V., “A new extension of hesitant fuzzy set: An application to an offshore wind turbine technology selection process”, IET Renewable Power Generation, 15(11): 2340-2355, (2021).
106. [106] Cui, L., Xu, Y., Xu, L. and Huang, G., “Wind Farm Location Special Optimization Based on Grid GIS and Choquet Fuzzy Integral Method in Dalian City, China”, Energies, 14(9): 2454, (2021).
107. [107] Güler, E. and Kandemir, S. Y., “Evaluation of Wind Power Plant Potentials in the Marmara Region, Turkey via TOPSIS and PROMETHEE Methods” 7th Iran Wind Energy Conference (IWEC2021), 1-4, IEEE, (2021).
108. [108] Caceoğlu, E., Yildiz, H. K., Oğuz, E., Huvaj, N. and Guerrero, J. M., “Offshore wind power plant site selection using Analytical Hierarchy Process for Northwest Turkey”, Ocean Engineering, 252, 111178, (2022).
109. [109] Dehshiri, S. S. H., “New hybrid multi criteria decision making method for offshore windfarm site location in Persian Gulf, Iran”, Ocean Engineering, 256, 111498, (2022).
110. [110] Salvador, C. B., Arzaghi, E., Yazdi, M., Jahromi, H. A. and Abbassi, R., “A multi-criteria decision-making framework for site selection of offshore wind farms in Australia”, Ocean & Coastal Management, 224, 106196, (2022).
111. [111] Hoang, T. N., Ly, T. T. B. and Do, H. T. T., “A hybrid approach of wind farm site selection using Group Best‐Worst Method and GIS‐Based Fuzzy Logic Relations. A case study in Vietnam”, Environmental Quality Management, (2022).
112. [112] Dhingra, T., Sengar, A. and Sajith, S., “A fuzzy analytic hierarchy process-based analysis for prioritization of barriers to offshore wind energy”, Journal of Cleaner Production, 345, 131111, (2022).
113. [113] Nguyen, V. T., Hai, N. H. and Lan, N. T. K., “Spherical fuzzy multicriteria decision-making model for wind turbine supplier selection in a renewable energy project”, Energies, 15(3), 713, (2022).