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Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods

Yıl 2024, , 291 - 308, 24.06.2024
https://doi.org/10.58559/ijes.1437059

Öz

This study focuses on various Multi-Criteria Decision Making (MCDM) methods developed in the academic literature to facilitate the decision-making process. These methods are primarily aimed at establishing a ranking of alternatives based on specific criteria, with the ultimate goal of determining the most optimal alternative. In this work, we propose a novel integrated MCDM approach that combines the Total Area Based on Orthogonal Vectors (TAOV) method with the Multi-Attribute Utility Theory (MAUT) method. Within this framework, criteria weights are determined using the MAUT method, while the TAOV method is employed to ascertain the ranking of alternatives. The primary objective of this approach is to identify the most suitable renewable energy resource for the context of Turkey. Based on a comprehensive review of relevant literature regarding the evaluation of renewable energy sources in Turkey, a set of critical criteria influencing the decision-making process is delineated. These criteria encompass a range of factors including efficiency, construction duration, cost, government incentives, economic lifespan, external dependence, employment opportunities, social acceptance, spatial requirements, and environmental considerations such as greenhouse gas emissions. The outcomes of this study reveal that, according to the proposed approach, the most beneficial renewable energy resources for Turkey are ranked as follows: hydroelectric, wind, solar, biomass, and geothermal energy sources, respectively.

Kaynakça

  • [1]Heo E, Kim J, Boo KJ. Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renewable and Sustainable Energy Reviews 2010; 14(8), 2214–2220. https://doi.org/10.1016/j.rser.2010.01.020.
  • [2] Frangopoulos CA, Keramioti DE. Multi-criteria evaluation of energy systems with sustainability considerations. Entropy 2010; 12(5), 1006–1020. https://doi.org/10.3390/e12051006.
  • [3]Amer M, Daim TU. Selection of Renewable Energy Technologies for a Developing County: A Case of Pakistan. Energy for Sustainable Development 2011; 15, 420-435. http://dx.doi.org/10.1016/j.esd.2011.09.001.
  • [4]Troldborg M, Heslop S, Hough RL. Assessing the sustainability of renewable energy technologies using multi-criteria analysis: Suitability of approach for national-scale assessments and associated uncertainties. Renewable and Sustainable Energy Reviews 2014 ; 39, 1173–1184. https://doi.org/10.1016/j.rser.2014.07.160.
  • [5] Özcan E, Ünlüsoy S, Eren T. Evaluation of renewable energy investment alternatives in Turkey using ANP AND TOPSIS methods. Selcuk University Journal of Engineering Science and Technology 2017 ; 5(2), 204–219. https://doi.org/10.15317/scitech.2017.82.
  • [6] Fishburn PC. Methods of estimating additive utilities. Management Science 1967 ; 13(7), 435–453. https://doi.org/10.1287/mnsc.13.7.435
  • [7] Fishburn PC, Keeney RL. Seven independence concepts and continuous multiattribute utility functions. Journal of Mathematical Psychology 1974; 11(3), 294–327. https://doi.org/10.1016/0022-2496(74)90024-8.
  • [8] Sanayei A, Farid Mousavi S, Abdi M, Mohaghar A. An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming. Journal of the Franklin Institute 2008; 345(7), 731–747. https://doi.org/10.1016/j.jfranklin.2008.03.005.
  • [9] Kim SK, Song O. A MAUT approach for selecting a dismantling scenario for the thermal column in KRR-1. Annals of Nuclear Energy 2009 ; 36(2), 145–150. https://doi.org/10.1016/j.anucene.2008.11.034.
  • [10]Freitas LV, Freitas APBR, Veraszto EV, Marins FAS, Silva MB. Decision-Making with Multiple Criteria Using AHP and MAUT:An Industrial Application. European International Journal of Science and Technology 2013 ; 2(9), 93-100.
  • [11] Ömürbek N, Karaatlı M, Balcı HF. Performance evaluation of automotive firms with entropy based MAUT and SAW methods. Dokuz Eylul University Journal of Economics and Administrative Sciences 2016 ; 31(1), 227–256. https://doi.org/10.24988/deuiibf.2016311446.
  • [12]Razavi SH, Amoozad H, Hashemi SS. Total area based on orthogonal vectors (TAOV) as a novel method of multi-criteria decision aid. Technological and Economic Development of Economy 2018; 24(4), 1679–1694. https://doi.org/10.3846/20294913.2016.1275877.
  • [13] Mokhtarzadeh N, Mahdiraji H, Beheshti M, Zavadskas E. A novel hybrid approach for technology selection in the information technology industry. Technologies 2018; 6(1), 34. https://doi.org/10.3390/technologies6010034.
  • [14] Jafari-Sadeghi V, Dutta DK, Ferraris A, Giudice M. Internationalization business processes in an under-supported policy contexts: evidence from Italian SMEs. Business Process Management Journal 2020; 26(5), 1055–1074. https://doi.org/10.1108/bpmj-03-2019-0141.
  • [15] Alagöz İ, Avşar Özcan N, Küçükyarar U. Özcan, E. Maintenance prioritization of the natural gas combined cycle power plants in terms of effective portfolio management. Journal of Polytechnic 2021; 24(3), 821–831. https://doi.org/10.2339/politeknik.716408.
  • [16] Güllü M, Kartal Z. Employment impact of renewable energy sources in Turkey. Sakarya Journal of Economics 2021; 10(1), 36–65. https://dergipark.org.tr/tr/pub/sid/issue/61134/849831.
  • [17]Ministry of Energy and Natural Resources. 2020; 2019-2023 Strategy Plan. https://sp.enerji.gov.tr/ETKB_2019_2023_Stratejik_Plani.pdf
  • [18]Ministry of Energy and Natural Resources. 2020; 2020 Activity Reports. https://enerji.gov.tr/Media/Dizin/SGB/tr/Faaliyet_Raporlari/2020/ETKB2020Y%C4%B1l% C4%B1%C4%B0dareFaaliyetRaporu.pdf
  • [19]Ministry of Energy and Natural Resources. 2020; 2019 Activity Reports.https://enerji.gov.tr/Media/Dizin/EIGM/tr/Raporlar/Ulusal_Enerji_Denge_Tablolari/ 2019.xlsx.
  • [20]British Petroleum Company. 2020; BP statistical review of world energy. London: British PetroleumCo. https://www.bp.com/content/dam/bp/businesssites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2020- full-report.pdf.
  • [21]Energy Market Regulatory Authority. 2020; Electricity market sector report. https://www.epdk.org.tr/Detay/Icerik/3-0-23-3/elektrikaylik-sektor-raporlar.
  • [22]Turkish Electricity Transmission Corporation. 2020; Turkish electricity transmission corporation activity report 2019. https://www.teias.gov.tr/faaliyet-raporlari.
Yıl 2024, , 291 - 308, 24.06.2024
https://doi.org/10.58559/ijes.1437059

Öz

Kaynakça

  • [1]Heo E, Kim J, Boo KJ. Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renewable and Sustainable Energy Reviews 2010; 14(8), 2214–2220. https://doi.org/10.1016/j.rser.2010.01.020.
  • [2] Frangopoulos CA, Keramioti DE. Multi-criteria evaluation of energy systems with sustainability considerations. Entropy 2010; 12(5), 1006–1020. https://doi.org/10.3390/e12051006.
  • [3]Amer M, Daim TU. Selection of Renewable Energy Technologies for a Developing County: A Case of Pakistan. Energy for Sustainable Development 2011; 15, 420-435. http://dx.doi.org/10.1016/j.esd.2011.09.001.
  • [4]Troldborg M, Heslop S, Hough RL. Assessing the sustainability of renewable energy technologies using multi-criteria analysis: Suitability of approach for national-scale assessments and associated uncertainties. Renewable and Sustainable Energy Reviews 2014 ; 39, 1173–1184. https://doi.org/10.1016/j.rser.2014.07.160.
  • [5] Özcan E, Ünlüsoy S, Eren T. Evaluation of renewable energy investment alternatives in Turkey using ANP AND TOPSIS methods. Selcuk University Journal of Engineering Science and Technology 2017 ; 5(2), 204–219. https://doi.org/10.15317/scitech.2017.82.
  • [6] Fishburn PC. Methods of estimating additive utilities. Management Science 1967 ; 13(7), 435–453. https://doi.org/10.1287/mnsc.13.7.435
  • [7] Fishburn PC, Keeney RL. Seven independence concepts and continuous multiattribute utility functions. Journal of Mathematical Psychology 1974; 11(3), 294–327. https://doi.org/10.1016/0022-2496(74)90024-8.
  • [8] Sanayei A, Farid Mousavi S, Abdi M, Mohaghar A. An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming. Journal of the Franklin Institute 2008; 345(7), 731–747. https://doi.org/10.1016/j.jfranklin.2008.03.005.
  • [9] Kim SK, Song O. A MAUT approach for selecting a dismantling scenario for the thermal column in KRR-1. Annals of Nuclear Energy 2009 ; 36(2), 145–150. https://doi.org/10.1016/j.anucene.2008.11.034.
  • [10]Freitas LV, Freitas APBR, Veraszto EV, Marins FAS, Silva MB. Decision-Making with Multiple Criteria Using AHP and MAUT:An Industrial Application. European International Journal of Science and Technology 2013 ; 2(9), 93-100.
  • [11] Ömürbek N, Karaatlı M, Balcı HF. Performance evaluation of automotive firms with entropy based MAUT and SAW methods. Dokuz Eylul University Journal of Economics and Administrative Sciences 2016 ; 31(1), 227–256. https://doi.org/10.24988/deuiibf.2016311446.
  • [12]Razavi SH, Amoozad H, Hashemi SS. Total area based on orthogonal vectors (TAOV) as a novel method of multi-criteria decision aid. Technological and Economic Development of Economy 2018; 24(4), 1679–1694. https://doi.org/10.3846/20294913.2016.1275877.
  • [13] Mokhtarzadeh N, Mahdiraji H, Beheshti M, Zavadskas E. A novel hybrid approach for technology selection in the information technology industry. Technologies 2018; 6(1), 34. https://doi.org/10.3390/technologies6010034.
  • [14] Jafari-Sadeghi V, Dutta DK, Ferraris A, Giudice M. Internationalization business processes in an under-supported policy contexts: evidence from Italian SMEs. Business Process Management Journal 2020; 26(5), 1055–1074. https://doi.org/10.1108/bpmj-03-2019-0141.
  • [15] Alagöz İ, Avşar Özcan N, Küçükyarar U. Özcan, E. Maintenance prioritization of the natural gas combined cycle power plants in terms of effective portfolio management. Journal of Polytechnic 2021; 24(3), 821–831. https://doi.org/10.2339/politeknik.716408.
  • [16] Güllü M, Kartal Z. Employment impact of renewable energy sources in Turkey. Sakarya Journal of Economics 2021; 10(1), 36–65. https://dergipark.org.tr/tr/pub/sid/issue/61134/849831.
  • [17]Ministry of Energy and Natural Resources. 2020; 2019-2023 Strategy Plan. https://sp.enerji.gov.tr/ETKB_2019_2023_Stratejik_Plani.pdf
  • [18]Ministry of Energy and Natural Resources. 2020; 2020 Activity Reports. https://enerji.gov.tr/Media/Dizin/SGB/tr/Faaliyet_Raporlari/2020/ETKB2020Y%C4%B1l% C4%B1%C4%B0dareFaaliyetRaporu.pdf
  • [19]Ministry of Energy and Natural Resources. 2020; 2019 Activity Reports.https://enerji.gov.tr/Media/Dizin/EIGM/tr/Raporlar/Ulusal_Enerji_Denge_Tablolari/ 2019.xlsx.
  • [20]British Petroleum Company. 2020; BP statistical review of world energy. London: British PetroleumCo. https://www.bp.com/content/dam/bp/businesssites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2020- full-report.pdf.
  • [21]Energy Market Regulatory Authority. 2020; Electricity market sector report. https://www.epdk.org.tr/Detay/Icerik/3-0-23-3/elektrikaylik-sektor-raporlar.
  • [22]Turkish Electricity Transmission Corporation. 2020; Turkish electricity transmission corporation activity report 2019. https://www.teias.gov.tr/faaliyet-raporlari.
Toplam 22 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Siyaset Bilimi (Diğer), Yenilenebilir Enerji Sistemleri
Bölüm Research Article
Yazarlar

Burhan Aydın 0000-0001-8983-3196

Özlem Ege Oruç 0000-0003-0984-5459

Yayımlanma Tarihi 24 Haziran 2024
Gönderilme Tarihi 14 Şubat 2024
Kabul Tarihi 10 Haziran 2024
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Aydın, B., & Ege Oruç, Ö. (2024). Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods. International Journal of Energy Studies, 9(2), 291-308. https://doi.org/10.58559/ijes.1437059
AMA Aydın B, Ege Oruç Ö. Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods. Int J Energy Studies. Haziran 2024;9(2):291-308. doi:10.58559/ijes.1437059
Chicago Aydın, Burhan, ve Özlem Ege Oruç. “Determining the Most Useful Renewable Energy Alternative for Turkey by Combining MAUT and TAOV Methods”. International Journal of Energy Studies 9, sy. 2 (Haziran 2024): 291-308. https://doi.org/10.58559/ijes.1437059.
EndNote Aydın B, Ege Oruç Ö (01 Haziran 2024) Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods. International Journal of Energy Studies 9 2 291–308.
IEEE B. Aydın ve Ö. Ege Oruç, “Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods”, Int J Energy Studies, c. 9, sy. 2, ss. 291–308, 2024, doi: 10.58559/ijes.1437059.
ISNAD Aydın, Burhan - Ege Oruç, Özlem. “Determining the Most Useful Renewable Energy Alternative for Turkey by Combining MAUT and TAOV Methods”. International Journal of Energy Studies 9/2 (Haziran 2024), 291-308. https://doi.org/10.58559/ijes.1437059.
JAMA Aydın B, Ege Oruç Ö. Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods. Int J Energy Studies. 2024;9:291–308.
MLA Aydın, Burhan ve Özlem Ege Oruç. “Determining the Most Useful Renewable Energy Alternative for Turkey by Combining MAUT and TAOV Methods”. International Journal of Energy Studies, c. 9, sy. 2, 2024, ss. 291-08, doi:10.58559/ijes.1437059.
Vancouver Aydın B, Ege Oruç Ö. Determining the most useful renewable energy alternative for Turkey by combining MAUT and TAOV methods. Int J Energy Studies. 2024;9(2):291-308.