Volume 23 , Issue 1 , PP: 216-229, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Edmundo Jalón Arias 1 * , Luis Freire Lescano 2 , Giovanny Pineda Silva 3 , Maha Ibrahim 4
Doi: https://doi.org/10.54216/IJNS.230119
In a power plant, the fuel choice directly impacts the efficiency, cost, and ecological impact of generating electricity. For power plants to produce electricity effectively and affordably to fulfill the needs of consumers in homes, companies, and communities, they need a fuel supply that is constant, dependable, and inexpensive. In this study, we used the concept of multi-criteria decision-making (MCDM) to deal with the various criteria of fuel alternatives. We used the EDAS method as an MCDM methodology to rank the fuel alternatives and select the best one. The EDAS method is employed with the interval-valued neutrosophic sets (IVNSs) to deal with the uncertainty information in the evaluation process. We compute the weights of the criteria of thermodynamic parameters. We used ten thermodynamic parameters such as temperature, mass, energy, etc. Then, the principal results show that temperature is the best criterion, and the work interaction is the worst criterion in all criteria. The EDAS method ranked twenty alternatives. The results show that alternative 20 are the best and alternative 14 is the worst of all alternatives. We employed the sensitivity analysis to show the rank of alternatives under ten cases. The results show the 20 alternative is the best in all cases. The results are stable.
Interval Valued Neutrosophic Sets , MCDM, EDAS Method , Thermal Power Station , Fuel Power , Energy.
[1] A. Di Gianfrancesco, “The fossil fuel power plants technology,” in Materials for ultra-supercritical and advanced ultra-supercritical power plants, Elsevier, 2017, pp. 1–49.
[2] E. S. Rubin, C. Chen, and A. B. Rao, “Cost and performance of fossil fuel power plants with CO2 capture and storage,” Energy policy, vol. 35, no. 9, pp. 4444–4454, 2007.
[3] M. D. Leonard, E. E. Michaelides, and D. N. Michaelides, “Energy storage needs for the substitution of fossil fuel power plants with renewables,” Renewable Energy, vol. 145, pp. 951–962, 2020.
[4] A. Mazandarani, T. M. I. Mahlia, W. T. Chong, and M. Moghavvemi, “Fuel consumption and emission prediction by Iranian power plants until 2025,” Renewable and Sustainable Energy Reviews, vol. 15, no. 3, pp. 1575–1592, 2011.
[5] E. I. Koytsoumpa et al., “The challenge of energy storage in Europe: focus on power to fuel,” Journal of Energy Resources Technology, vol. 138, no. 4, p. 42002, 2016.
[6] P. Oskarsson, K. B. Nielsen, K. Lahiri-Dutt, and B. Roy, “India’s new coal geography: Coastal transformations, imported fuel and state-business collaboration in the transition to more fossil fuel energy,” Energy Research & Social Science, vol. 73, p. 101903, 2021.
[7] H. Hou, J. Wu, Y. Yang, E. Hu, and S. Chen, “Performance of a solar aided power plant in fuel saving mode,” Applied Energy, vol. 160, pp. 873–881, 2015.
[8] I. H. Aljundi, “Energy and exergy analysis of a steam power plant in Jordan,” Applied thermal engineering, vol. 29, no. 2–3, pp. 324–328, 2009.
[9] P. Thounthong, A. Luksanasakul, P. Koseeyaporn, and B. Davat, “Intelligent model-based control of a standalone photovoltaic/fuel cell power plant with supercapacitor energy storage,” IEEE Transactions on Sustainable Energy, vol. 4, no. 1, pp. 240–249, 2012.
[10] A. M. Wolsky, E. J. Daniels, and B. J. Jody, “CO2 capture from the flue gas of conventional fossil‐fuel‐fired power plants,” Environmental Progress, vol. 13, no. 3, pp. 214–219, 1994.
[11] V. Tzelepi et al., “Biomass availability in europe as an alternative fuel for full conversion of lignite power plants: A critical review,” Energies, vol. 13, no. 13, p. 3390, 2020.
[12] K. Park, D. Shin, and E. S. Yoon, “The cost of energy analysis and energy planning for emerging, fossil fuel power plants based on the climate change scenarios,” Energy, vol. 36, no. 5, pp. 3606–3612, 2011.
[13] N. Zhang, F. Kong, Y. Choi, and P. Zhou, “The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants,” Energy policy, vol. 70, pp. 193–200, 2014.
[14] D. Neshumayev, L. Rummel, A. Konist, A. Ots, and T. Parve, “Power plant fuel consumption rate during load cycling,” Applied Energy, vol. 224, pp. 124–135, 2018.
[15] W. R. Dunbar, N. Lior, and R. A. Gaggioli, “Combining fuel cells with fuel-fired power plants for improved exergy efficiency,” Energy, vol. 16, no. 10, pp. 1259–1274, 1991.
[16] A. Karaşan and C. Kahraman, “Interval-valued neutrosophic extension of EDAS method,” in Advances in Fuzzy Logic and Technology 2017: Proceedings of: EUSFLAT-2017–The 10th Conference of the European Society for Fuzzy Logic and Technology, September 11-15, 2017, Warsaw, Poland IWIFSGN’2017–The Sixteenth International Workshop on Intuitionistic, Springer, 2018, pp. 343–357.
[17] N. Nabeeh, “Assessment and Contrast the Sustainable Growth of Various 1 Road Transport Systems using Intelligent Neutrosophic 2 Multi-Criteria Decision-Making Model,” Sustainable Machine Intelligence Journal, vol. 2, 2023.
[18] A. Karaşan and C. Kahraman, “A novel interval-valued neutrosophic EDAS method: prioritization of the United Nations national sustainable development goals,” Soft Computing, vol. 22, pp. 4891–4906, 2018.
[19] M. Mohamed and K. M. Sallam, “Leveraging Neutrosophic Uncertainty Theory toward Choosing Biodegradable Dynamic Plastic Product in Various Arenas,” Neutrosophic Systems with Applications, vol. 5, pp. 1–9, 2023.
[20] J.-P. Fan, R. Cheng, and M.-Q. Wu, “Extended EDAS methods for multi-criteria group decision-making based on IV-CFSWAA and IV-CFSWGA operators with interval-valued complex fuzzy soft information,” Ieee Access, vol. 7, pp. 105546–105561, 2019.
[21] Alber S. Aziz, Moahmed Emad, Mahmoud Ismail, Heba Rashad, Ahmed M. Ali, Ahmed Abdelhafeez, Shimaa S. Mohamed, An Intelligent Multi-Criteria Decision-Making Model for selecting an optimal location for a data center: Case Study in Egypt, Journal of Intelligent Systems and Internet of Things, Vol. 9 , No. 2 , (2023) : 23-35 (Doi : https://doi.org/10.54216/JISIoT.090202
[22] Tamer H. M. Soliman, Neutrosophic Multi-Criteria Decision Making COMET Method for Evaluation Sustainable Electricity Generation Considering Renewable Energy Sources, International Journal of Advances in Applied Computational Intelligence, Vol. 4 , No. 1 , (2023) : 19-27 Doi : https://doi.org/10.54216/IJAACI.040102
[23] Y. Li, J. Wang, and T. Wang, “A linguistic neutrosophic multi-criteria group decision-making approach with EDAS method.,” Arabian Journal for Science & Engineering (Springer Science & Business Media BV), vol. 44, no. 3, 2019.
[24] Ahmed Abdelhafeez, Hoda K. Mohamed, Skin Cancer Detection using Neutrosophic c-means and Fuzzy c-means Clustering Algorithms, Journal of Intelligent Systems and Internet of Things, Vol. 8 , No. 1 , (2023) : 33-42 (Doi : https://doi.org/10.54216/JISIoT.080103)
[25] A. Karaşan, C. Kahraman, and E. Boltürk, “Interval-valued neutrosophic EDAS method: an application to prioritization of social responsibility projects,” in Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets, Springer, 2019, pp. 455–485.
[26] D. Stanujkić et al., “A single-valued neutrosophic extension of the EDAS method,” Axioms, vol. 10, no. 4, p. 245, 2021.
[27] S. Ashraf, S. Ahmad, M. Naeem, M. Riaz, and M. Alam, “Novel EDAS methodology based on single-valued neutrosophic Aczel-Alsina aggregation information and their application in complex decision-making,” Complexity, vol. 2022, 2022.
[28] J. Fan, X. Jia, and M. Wu, “A new multi-criteria group decision model based on Single-valued triangular Neutrosophic sets and EDAS method,” Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 2089–2102, 2020.
[29] E. Cakmak, “Supplier Selection for a Power Generator Sustainable Supplier Park: Interval-Valued Neutrosophic SWARA and EDAS Application,” Sustainability, vol. 15, no. 18, p. 13973, 2023.
[30] S. Al-Saeed and N. M. AbdelAziz, “Integrated Neutrosophic Best-Worst Method for Comprehensive Analysis and Ranking of Flood Risks: A Case Study Approach from Aswan, Egypt,” Neutrosophic Systems with Applications, vol. 5, pp. 10–26, 2023.
[31] D. Xu, X. Cui, and H. Xian, “An extended EDAS method with a single-valued complex neutrosophic set and its application in green supplier selection,” Mathematics, vol. 8, no. 2, p. 282, 2020.
[32] Alber S. Aziz, Neutrosophic Combinative Distance-based Assessment (CODAS) Method for Evaluating the Financial and Operational Performance of Shipping Companies, International Journal of Advances in Applied Computational Intelligence, Vol. 4 , No. 1 , (2023) : 28-36, Doi :https://doi.org/10.54216/IJAACI.040103
[33] L. Han and C. Wei, “An extended EDAS method for multicriteria decision-making based on multivalued neutrosophic sets,” Complexity, vol. 2020, pp. 1–9, 2020.
