2692-2967ISSN (Online)
2770-0216ISSN (Print)
Volume 10 , Issue 2 , PP: 14-22, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Ahmed M. Ali 1 * , Ahmed Abdelmouty 2
Doi: https://doi.org/10.54216/AJBOR.100202
While it is still in its infancy in comparison to other forms of renewable technology, there is a growing amount of interest and backing for wave energy as a potentially useful renewable resource that could replace a portion of the existing energy supply. In the context of sustainable development, the choice of technology represents a multi-criterion decision-making (MCDM) challenge that may affect the competitive advantages enjoyed by an organization or a nation. The purpose of this study is to evaluate the many wave energy technologies that are now in use as possible choices for green and sustainable technologies that may be used in the seas and oceans. However, requirements like ecological, financial, and technological factors that are based on the fundamental idea of sustainability calls for unclear or unreliable expert assessments that can be solved using single-valued neutrosophic sets (SVNSs). Because of this, the selection of sustainable wave energy technology requires the creation of a one-of-a-kind framework that can analyze both clear and ambiguous data simultaneously without sacrificing any of the information in either category. This study developed a framework that uses measurement alternatives and ranking based on compromise solution (MARCOS) within the context of SVNSs to assist decision-makers in the process of resolving real-time energy problems. An application of the process of selecting the wave energy technology is taken into consideration here as a means of illustrating how applicable the suggested framework is.
, Single-Valued Neutrosophic Sets , MCDM , Renewable Energy , Wave Energy Technology.
[1] S. Nasrollahi, A. Kazemi, M.-H. Jahangir, and S. Aryaee, “Selecting suitable wave energy technology for sustainable development, an MCDM approach,” Renew. Energy, vol. 202, pp. 756–772, 2023.
[2] I. López, J. Andreu, S. Ceballos, I. M. De Alegría, and I. Kortabarria, “Review of wave energy technologies and the necessary power-equipment,” Renew. Sustain. energy Rev., vol. 27, pp. 413–434, 2013.
[3] B. Drew, A. R. Plummer, and M. N. Sahinkaya, “A review of wave energy converter technology.” Sage Publications Sage UK: London, England, 2009.
[4] T. W. Thorpe, “An overview of wave energy technologies: status, performance and costs,” Wave power Mov. Towar. Commer. viability, vol. 26, pp. 50–120, 1999.
[5] A. F. de O. Falcão, “Wave energy utilization: A review of the technologies,” Renew. Sustain. energy Rev., vol. 14, no. 3, pp. 899–918, 2010.
[6] T. Aderinto and H. Li, “Ocean wave energy converters: Status and challenges,” Energies, vol. 11, no. 5, p. 1250, 2018.
[7] S. Ghosh, T. Chakraborty, S. Saha, M. Majumder, and M. Pal, “Development of the location suitability index for wave energy production by ANN and MCDM techniques,” Renew. Sustain. Energy Rev., vol. 59, pp. 1017–1028, 2016.
[8] C.-N. Wang, Y.-T. Chen, and C.-C. Tung, “Evaluation of wave energy location by using an integrated MCDM approach,” Energies, vol. 14, no. 7, p. 1840, 2021.
[9] İ. Kaya, M. Çolak, and F. Terzi, “Use of MCDM techniques for energy policy and decision‐making problems: A review,” Int. J. Energy Res., vol. 42, no. 7, pp. 2344–2372, 2018.
[10] T. Chakraborty, “A MCDM-NBO approach for selection of installation location for wave energy power plants,” Appl. Geogr. Inf. Syst. soft Comput. Tech. water water based Renew. energy Probl., pp. 121–140, 2018.
[11] M. Çolak and İ. Kaya, “Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey,” Renew. Sustain. energy Rev., vol. 80, pp. 840–853, 2017.
[12] S. Ghosh, “Wave energy potential site selection based on MCDM and neural network analysis,” Appl. Geogr. Inf. Syst. Soft Comput. Tech. Water Water Based Renew. Energy Probl., pp. 107–120, 2018.
[13] M. Shao, Z. Han, J. Sun, S. Zhang, Y. Zhao, and Z. Shao, “A GIS-MCDM Combination for the Site Assessment of Wave Energy Power Station in Qingdao, Eastern China,” in The 30th International Ocean and Polar Engineering Conference, OnePetro, 2020.
[14] D. Zhang, W. Li, and Y. Lin, “Wave energy in China: Current status and perspectives,” Renew. energy, vol. 34, no. 10, pp. 2089–2092, 2009.
[15] J. V Ringwood, G. Bacelli, and F. Fusco, “Energy-maximizing control of wave-energy converters: The development of control system technology to optimize their operation,” IEEE Control Syst. Mag., vol. 34, no. 5, pp. 30–55, 2014.
[16] W. Sheng, “Wave energy conversion and hydrodynamics modelling technologies: A review,” Renew. Sustain. Energy Rev., vol. 109, pp. 482–498, 2019.
[17] D. Pamucar, F. Ecer, and M. Deveci, “Assessment of alternative fuel vehicles for sustainable road transportation of United States using integrated fuzzy FUCOM and neutrosophic fuzzy MARCOS methodology,” Sci. Total Environ., vol. 788, p. 147763, 2021.
[18] Y. Rong, W. Niu, H. Garg, Y. Liu, and L. Yu, “A hybrid group decision approach based on MARCOS and regret theory for pharmaceutical enterprises assessment under a single-valued neutrosophic scenario,” Systems, vol. 10, no. 4, p. 106, 2022.
[19] P. Majumder, “An Integrated Trapezoidal Fuzzy FUCOM with Single-valued Neutrosophic Fuzzy MARCOS and GMDH Method to Determine the Alternatives Weight and its Applications in Efficiency Analysis of Water Treatment Plant,” Expert Syst. Appl., p. 120087, 2023.
[20] V. Simic, I. Gokasar, M. Deveci, and L. Švadlenka, “Mitigating Climate Change Effects of Urban Transportation Using a Type-2 Neutrosophic MEREC-MARCOS Model,” IEEE Trans. Eng. Manag., 2022.
[21] J. Fan, S. Zhai, and M. Wu, “PT-MARCOS multi-attribute decision-making method under neutrosophic cubic environment,” J. Intell. Fuzzy Syst., vol. 42, no. 3, pp. 1737–1748, 2022.
[22] N. Tang, B. Li, and M. Elhoseny, “Assessment of English teaching systems using a single-valued neutrosophic MACROS method,” Neutrosophic Sets Syst., vol. 46, pp. 87–110, 2021.
[23] E. Çakır, M. A. Taş, and Z. Ulukan, “Neutrosophic fuzzy MARCOS approach for sustainable hybrid electric vehicle assessment,” in 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, 2021, pp. 3423–3428.
[24] R. S. U. Haq et al., “Sustainable material selection with crisp and ambiguous data using single-valued neutrosophic-MEREC-MARCOS framework,” Appl. Soft Comput., vol. 128, p. 109546, 2022.
