Journals / Alphanumeric Journal / 2026 / Volume: 6 Issue: 1

Sustainable and Renewable Energy Power Plants Evaluation by Fuzzy TODIM Technique

Sürdürülebilir ve Yenilenebilir Enerji Santrallerinin Bulanık TODIM Yöntemiyle Değerlendirilmesi

Pages
—
Publication Date
2018-03-26
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally we evaluated the results obtained and presented a sensitivity analysis at the end.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Sustainable and renewable energy systems are an effective solution to depletion of fossil energy resources and prevent serious environmental problems resulted from energy production.
📊
Key Findings & Data:In this regard, the government puts emphasis on increasing renewable energy utilization rate in meeting energy demand of the country.
💡
Conclusion & Impact:Finally we evaluated the results obtained and presented a sensitivity analysis at the end.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:fuzzy TODIM · prospect theory · power plants

Abstract

Sustainable and renewable energy systems are an effective solution to depletion of fossil energy resources and prevent serious environmental problems resulted from energy production. Turkey has rich renewable energy potential due to its geographical features. In this regard, the government puts emphasis on increasing renewable energy utilization rate in meeting energy demand of the country. Therefore encouragement policies are implemented in this field and energy investors are supported economically. In his study, we aimed to find out the best performing sustainable and renewable energy alternative and thus to guide decision makers on energy investments. Therefore we evaluated four energy power plant types, which are solar, wind, hydroelectric and landfilled gas (LFG). For the evaluation of the alternatives, there are many factors to consider and multicriteria decision making (MCDM) methods are an appropriate approach for this issue. In this regard, we determined 22 evaluation criteria in technical, economical and environmental aspect and applied TODIM technique. It is based on prospect theory and the most significant difference from the other MCDM methods is to deal with risk in decision-making. In order to cope with vagueness and uncertainty in this evaluation process, we integrated fuzzy sets into the system. Finally we evaluated the results obtained and presented a sensitivity analysis at the end.

Özet

Sürdürülebilir ve yenilenebilir enerji kaynakları, fosil enerji kaynaklarının azalmasına ve enerji üretiminden kaynaklanan ciddi çevresel problemlerin oluşmasına karşı etkili bir çözümdür. Türkiye coğrafi özellikleri bakımından zengin yenilenebilir enerji potansiyeline sahiptir. Bu bağlamda kendi enerji ihtiyacının karşılanmasında yenilenebilir enerji kaynaklarının payının artmasına önem vermektedir. Bunun için bu alanda teşvik çalışmaları yapılmakta ve yatırımcılar ekonomik olarak desteklenmektedir. Buradan hareketle, bu çalışmada alternatifler arasından en iyi performans gösteren sürdürülebilir ve yenilenebilir enerji çeşidini bulmak ve bu sayede enerji yatırımlarına referans kaynağı olmak amaçlanmıştır. Dört enerji santral alternatifi değerlendirilmiştir; bunlar güneş, rüzgar, hidroelektrik ve LFG (çöp gazı) santralleridir. Alternatifler değerlendirildiğinde göz önünde bulundurulması gereken birçok önemli kriter bulunmaktadır ve bu problem çeşidi için çok ölçütlü karar verme (ÇÖKV) sistemlerinin uygulanması yerinde bir yaklaşımdır. Bunun üzerine teknik, ekonomik ve çevresel açıdan toplam 22 değerlendirme kriteri belirlenmiştir ve yöntem olarak TODIM tekniği uygulanmıştır. TODIM beklenti teorisine dayanan bir ÇÖKV tekniğidir ve diğer yöntemlerden en önemli farkı karar verme mekanizmasında risk faktörünü ele almasıdır. Ayrıca çalışmada belirsiz, muğlak ve müphem durumlara karşı çözüm için bulanık kümeler sisteme entegre edilmiştir. Elde edilen sonuçlar değerlendirilmiş ve çalışmanın sonunda duyarlılık analizine yer verilmiştir.

🔖

Cite This Article

Tolga, A. Ç., Turgut, Z. K. (2018). Sustainable and Renewable Energy Power Plants Evaluation by Fuzzy TODIM Technique. Alphanumeric Journal, Volume: 6 Issue: 1. https://doi.org/10.17093/alphanumeric.371754

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (57)

  1. Abdel-Kader, M.G. and Dugdale, D. (2001). Evaluating investments in advanced manufacturing technology: a fuzzy set theory approach. Br. Account. Rev. 33, 455-489
  2. Adalı, E.A. (2016). Todim Method For The Selection Of The Elective Courses. European Scientific Journal, 314-324
  3. Araujo, R.M. (2015). Multicriteria Classification with TODIM-FSE. Procedia Computer Science, 55, 559-565
  4. Chang, T. H. (2014). Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Information Sciences: 271: 196-2
  5. Chen, S. J., Hwang, C. L., Hwang, F. P. (19929. Fuzzy Multiple Attribute Decision Making Methods and Applications, Berlin: Springer-Verlag, pp. 88-89
  6. Ekhtiari, M., Yadegari, E., Sadidi, G. (2016). Ranking enterpreneurship main risks in non-profit financial funds by todim technique under grey conditions (a case study in Iran). Economic Computation and Economic Cybernetics Studies and Research, 50(3), 319-336
  7. European Environment Agency. (1999). Environment in the European Union at the turn of the century: Summary. pp. 1-43
  8. Gao, S., Zhang, Z., Cao, C. (2009). Multiplication Operation on Fuzzy Numbers. Journal Of Software.:4(4): 331-338
  9. Gomes, C.F.S., Gomes, L.F.A.M., Maranhao, F.J.C. (2010). Decision analysis for the exploration of gas reserves: merging todim and thor. Pesquisa Operacional, 30(3), 601-617
  10. Gomes, L.F.A.M. and Lima M.M.P.P. (1992). From modeling individual preferences to multicriteria ranking of discrete alternatives: A look at Prospect Theory and the additive difference model, Foundations of Computing and Decision Sciences, 17(3),171– 184
  11. Gomes, L.F.A.M. and Rangel, L.A.D. (2009). An application of the TODIM method to the multicriteria rental evaluation of residential properties. European Journal of Operational Research,193, 204–211
  12. Gomes, L.F.A.M., Machado, M.A.S., Santos, D.J., Caldeira, A.M. (2015). Ranking of Suppliers for a Steel Industry: A Comparison of the Original TODIM and the Choquet-extended TODIM Methods. Procedia Computer Science, 55, 706-714
  13. Gürbüz, Ö. Türkiye kömür sevdası yüzünden tarihi fırsatı kaçırıyor. [Online]. Available: http://www.bbc.com/turkce/haberler-turkiye-40565449, [Accessed: 11-Jul-2017]
  14. Hanine, M., Boutkhoum, O., Tikniouine, A., Agouti, T. (2016). Comparison of fuzzy AHP and fuzzy TODIM methods for land fill location selection. SpringerPlus:5: 1-30
  15. Henley, B. and Abram, N. This is what ancient, 3km long ice cores tell us about climate change.[Online]. Available:
  16. https://www.weforum.org/agenda/2017/06/800-000-years-of-climate-change-in-3-minutes, [Accessed: 19-Jun-2017].
  17. Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica:47(2): 263-291
  18. Kahraman, C., Çevik, S., Öztayşi, B. (2015). Fuzzy Multicriteria Decision Making: A literature review. International Journal of Computational Intelligence Systems: 8(4): 637-666, DOI: 10.1080/18756891.2015.1046325
  19. Krohling, R.A. and Souza, T.T.M. (2012). Combining prospect theory and fuzzy numbers to multi-criteria decision making. Expert Systems with Applications:39: 11487–11493
  20. Krohling, R.A., Pacheco, A.B.C., Siviero, A.V.T. (2013). IF-TODIM An intuitionistic fuzzy TODIM to multi-criteria decision making. Elsevier Knowledge-Based Systems, 53, 142-146
  21. Li, M., Wu, C., Zhang, L., You, L.N. (2015). An intuitionistic fuzzy-todim method to solve distributor evaluation and selection problem. Int j simul model, 14(3), 511-524
  22. Liu P. and Teng, F. (2014). An Extended TODIM Method for Multiple Attribute Group Decision-Making Based on 2-Dimension Uncertain Linguistic Variable. Wiley Online Library, 21(5), 20-30
  23. Lourenzutti, R. and Krohling, R.A. (2013). A study of TODIM in a intuitionistic fuzzy and random environment. Expert Systems with Applications, 40(16), 6459-6468
  24. Lowe, J. A., Huntingford, C., Raper, S.C.B., Jones, C.D., Liddicot, S. K. and Gohar, L. K. (2009). How difficult is it to recover from dangerous levels of global warming?. IOPScience Environmental Research Letters:4:1-9
  25. Nobre, F.F., Trotta, L.T.F., Gomes, L. F. A. M.,(1999). Multi-criteria decision making - An approach to setting priorities in health care. Statistics in Medicine:18(23): 3345-3354
  26. Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert System with Applications:38 (10): 12983-12990
  27. Qin, Q., Liang, F., Li, L., Wei, Y. (2017). Selection of energy performance contracting business models: A behavioral decision-making approach. Renewable and Sustainable Energy Reviews, 72, 422-433
  28. Qin, Q., Liang, F., Li, L., Wei, Y., Yu, G. F. (2017). A TODIM-based multi-criteria group decision making with triangular intuitionistic fuzzy numbers. Applied soft computing, 55, 93-107
  29. Qin, Q., Liang, F., Chen, Y.W., Yu, G.F. (2017). A TODIM-based multi-criteria group decision making with triangular intuitionistic fuzzy numbers. Applied Soft Computing: 55: 93–107
  30. Rangel, L., Gomes, L., Cardoso, F. (2011). An Application Of The TODIM Method To The Evaluation Of Broadband Internet Plans. Pesquisa Operacional.:31(2): 235-249
  31. Ren, P., Xu, Z., Gou, X. (2016). Pythagorean fuzzy TODIM approach to multi-criteria decision making. Applied Soft Computing, 42, 246-259
  32. Ruzgys, A., Volvačiovas, R., Ignatavičius, C., Turskis, Z. (2014). Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method. Journal of Civil Engineering and Management, 20 (1), 103-110
  33. Sen, D. K., Datta, S., Patel, S. K., Mahapatra, S.S. (2016). Fuzzy-TODIM for Industrial Robot Selection. International Conference on Emerging Trends in Mechanical Engineering. 1-8
  34. Tasri, A. and Susilawati, A. (2014). Selection among renewable energy alternatives based on a fuzzy analytic hierarchy process in Indonesia. Sustainable Energy Technologies and Assessments:7: 34-44
  35. Tosun, Ö. and Akyüz, G. (2015). A fuzzy TODIM approach for the supplier selection problem. International Journal of Computational Intelligent Systems.:8(2): 317–329
  36. Turgut, Z. K. and Tolga, A. Ç. (2017). Sustainable and Renewable Energy Power Plants Evaluation by Fuzzy VIKOR Technique. Proceedings of the International MultiConference of Engineers and Computer Scientists, IMECS 2017, Hong Kong, 774-779
  37. Yanwei, L., Yuqing, S., Peide, L. (2015). An Extended TODIM Method for Group Decision Making with the Interval Intuitionistic Fuzzy Sets, Mathematical Problems in Engineering, 1-9
  38. Yıldırım, L., Ata, G., Taşkın, O., Lale, T. (2014). Sera Gazı Salınımları ve Türkiye’ de Yapılan Çalışmalar. Su Dünyası, Vol. 135 URL: http://www2.dsi.gov.tr/sudunyasi/135/index.html
  39. Zadeh, L. A. (1965).Fuzzy Sets. Information and Control:8,:338-353
  40. Zadeh, L. A. (1975). The concept f a linguistic variable and its application to approximate reasoning-I. Information Sciences:8: 199-249
  41. Saaty, T.L. (1980). The analytic hierarchy process. New York: McGraw-Hill
  42. Zhang, X. and Fan, Z. P. (2011). A method for linguistic multiple attribute decision making based on TODIM. International Conference on Management and Service Science. 1-4.
  43. Chang, T. H. (2014). Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Information Sciences: 271: 196-2
  44. Gao, S., Zhang, Z., Cao, C. (2009). Multiplication Operation on Fuzzy Numbers. Journal Of Software.:4(4): 331-338
  45. Hanine, M., Boutkhoum, O., Tikniouine, A., Agouti, T. (2016). Comparison of fuzzy AHP and fuzzy TODIM methods for land fill location selection. SpringerPlus:5: 1-30
  46. Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica:47(2): 263-291
  47. Kahraman, C., Çevik, S., Öztayşi, B. (2015). Fuzzy Multicriteria Decision Making: A literature review. International Journal of Computational Intelligence Systems: 8(4): 637-666, DOI: 10.1080/18756891.2015.1046325
  48. Krohling, R.A. and Souza, T.T.M. (2012). Combining prospect theory and fuzzy numbers to multi-criteria decision making. Expert Systems with Applications:39: 11487–11493
  49. Lowe, J. A., Huntingford, C., Raper, S.C.B., Jones, C.D., Liddicot, S. K. and Gohar, L. K. (2009). How difficult is it to recover from dangerous levels of global warming?. IOPScience Environmental Research Letters:4:1-9
  50. Nobre, F.F., Trotta, L.T.F., Gomes, L. F. A. M.,(1999). Multi-criteria decision making - An approach to setting priorities in health care. Statistics in Medicine:18(23): 3345-3354
  51. Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert System with Applications:38 (10): 12983-12990
  52. Qin, Q., Liang, F., Chen, Y.W., Yu, G.F. (2017). A TODIM-based multi-criteria group decision making with triangular intuitionistic fuzzy numbers. Applied Soft Computing: 55: 93–107
  53. Rangel, L., Gomes, L., Cardoso, F. (2011). An Application Of The TODIM Method To The Evaluation Of Broadband Internet Plans. Pesquisa Operacional.:31(2): 235-249
  54. Tasri, A. and Susilawati, A. (2014). Selection among renewable energy alternatives based on a fuzzy analytic hierarchy process in Indonesia. Sustainable Energy Technologies and Assessments:7: 34-44
  55. Tosun, Ö. and Akyüz, G. (2015). A fuzzy TODIM approach for the supplier selection problem. International Journal of Computational Intelligent Systems.:8(2): 317–329
  56. Zadeh, L. A. (1965).Fuzzy Sets. Information and Control:8,:338-353
  57. Zadeh, L. A. (1975). The concept f a linguistic variable and its application to approximate reasoning-I. Information Sciences:8: 199-249