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THE SELECTION OF TERRESTRIAL RENEWABLE ENERGY POWER PLANTS IN AN INTUITIONISTIC FUZZY ENVIRONMENT: THE CASE OF TURKEY

Yıl 2022, , 1230 - 1249, 28.12.2022
https://doi.org/10.17130/ijmeb.1133596

Öz

Energy is recognized as a significant indication of economic developmentin the globalizing globe. A society has to have plenty of energy resources in order to ensure sustainable development. These energy sources must be acquired at a reasonable cost and utilised to meet all societal demands without having a detrimental social impact. Power plants are often regarded as the center of the power producing business in all countries. It is crucial to the industry's and economy's survival. More power plants are required due to the requirement for energy supply and rising demand. Choosing the best power plant gives economic benefits, local employment, and energy security while decreasing environmental effect and resource waste. As a result, selecting the correct power plant for energy investments is critical. In this study, terrestrial renewable energy plants are ranked utilizing the intuitionistic fuzzy WASPAS approach. Economic, environmental, technological, and social criteria are taken into account while determining the best terrestrial renewable power facilities for Turkey. The solar power plant emerged as the most suitable renewable energy plant as a result of the modeling.

Destekleyen Kurum

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Proje Numarası

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Teşekkür

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Kaynakça

  • Adhikary, P., Roy, P. K., & Mazumdar, A. (2015). Maintenance contractor selection for small hydropower project: a fuzzy multi-criteria optimization technique approach. International Review of Mechanical Engineering, 9(2), 174-181.
  • Ahmad, S., & Tahar, R. M. (2014). Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: A case of Malaysia. Renewable energy, 63, 458-466.
  • Alizadeh, R., Soltanisehat, L., Lund, P. D., & Zamanisabzi, H. (2020). Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy, 137, 111174.
  • Amer, M., & Daim, T. U. (2011). Selection of renewable energy technologies for a developing county: a case of Pakistan. Energy for sustainable development, 15(4), 420-435.
  • Arda, Z., & Çavşi, H. (2018). Türkiye’deki jeotermal enerji santrallerinin durumu. Mühendis ve Makina, 59(691), 45-58. Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems.20(1), 87-96.
  • Balin, A., & Baraçli, H. (2017). A fuzzy multi-criteria decision making methodology based upon the interval type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey. Technological and Economic Development of Economy, 23(5), 742-763.
  • Buyukozkan, G., & Guleryuz, S. (2016). Fuzzy multi criteria decision making approach for evaluating sustainable energy technology alternatives. International journal of renewable energy sources, 1, 1-6.
  • Büyüközkan, G., & Güleryüz, S. (2016). An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. International journal of production economics, 182, 435-448.
  • Çelikbilek, Y., & Tüysüz, F. (2016). An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. Energy, 115, 1246-1258.
  • Damgaci, E., Boran, K., & Boran, F. (2017). Evaluation of Turkey's Renewable Energy Using Intuitionistic Fuzzy TOPSIS Method. Journal of polytechnic-Politeknik Dergisi
  • Erdal, L. (2012). Türkiye’de yenilenebilir enerji yatırımları ve istihdam yaratma potansiyeli. Sosyal ve Beşeri Bilimler Dergisi, 4(1), 171-181.
  • Ertay, T., Kahraman, C., & Kaya, İ. (2013). Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey. Technological and economic development of economy, 19(1), 38-62.
  • Ervural, B. C., Zaim, S., Demirel, O. F., Aydin, Z., & Delen, D. (2018). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews, 82, 1538-1550.
  • Gaoa, H., Ernesto, Y., Gonzalez, S., Zhang, W.(2020).Green supplier selection in electronics manufacturing: An approach based on consensus decision making. Journal of Cleaner Production. 245,118781. Gunter, Y. (2019). Sezgisel bulanık Kümelere Dayalı Çok Kriterli Karar Verme Yöntemleri. Yüksek Lisans Tezi, Selçuk Üniversitesi Fen Bilimleri Enstitüsü, İstatistik Anabilim Dalı.
  • Kahraman, C., Kaya, İ., & Cebi, S. (2009). A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process. Energy, 34(10), 1603-1616.
  • Katal, F., & Fazelpour, F. (2018). Multi-criteria evaluation and priority analysis of different types of existing power plants in Iran: An optimized energy planning system. Renewable Energy, 120, 163-177.
  • Lee, H. C., & Chang, C. T. (2018). Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews, 92, 883-896.
  • Memari, A., Dargi, A., Jokar, M. R. A., Ahmad, R., & Rahim, A. R. A. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of manufacturing systems, 50, 9-24.
  • Mishra, A. R., & Rani, P. (2018). Interval-valued intuitionistic fuzzy WASPAS method: Application in reservoir flood control management policy. Group Decision and Negotiation, 27(6), 1047-1078.
  • Mishra, A. R., Rani, P., Pardasani, K. R., & Mardani, A. (2019). A novel hesitant fuzzy WASPAS method for assessment of green supplier problem based on exponential information measures. Journal of Cleaner Production, 238, 117901.
  • Özkale, C., Celik, C., Turkmen, A. C., & Cakmaz, E. S. (2017). Decision analysis application intended for selection of a power plant running on renewable energy sources. Renewable and sustainable energy reviews, 70, 1011-1021.
  • Rahman, A., Farrok, O., & Haque, M. M. (2022). Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic. Renewable and Sustainable Energy Reviews, 161, 112279.
  • Sadeghi, A., Larimian, T., & Molabashi, A. (2012). Evaluation of renewable energy sources for generating electricity in province of Yazd: a fuzzy MCDM approach. Procedia-Social and Behavioral Sciences, 62, 1095-1099.
  • Štreimikienė, D., Šliogerienė, J., & Turskis, Z. (2016). Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable energy, 85, 148-156.
  • Tian, G., Zhang, H., Feng, Y., Wang, D., Peng, Y., & Jia, H. (2018). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, 81, 682-692.
  • Tirmikcioglu, N. (2021). Sezgisel Bulanık WASPAS Yöntemi ve Depo Yeri Seçimi Problemi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 21(6), 1330-1342.
  • Troldborg, M., Heslop, S., & Hough, R. L. (2014). 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, 39, 1173-1184.
  • Turgut, Z. K. (2017). Sustainable and renewable energy power palnts evaluation ve fuzzy VIKOR and fuzzy TODIM technıques. Galatasaray Üniversitesi, Fen Bilimleri Enstitüsü (Master Thesis)
  • Yazdani, M., Torkayesh, A. E., Santibanez-Gonzalez, E. D., & Otaghsara, S. K. (2020). Evaluation of renewable energy resources using integrated Shannon Entropy—EDAS model. Sustainable Operations and Computers, 1, 35-42.
  • Yildirim, B. F., & Ciftci, H. N. (2020). BIST’te İşlem Gören Tekstil Firmalarının Finansal Performanslarının Dinamik Sezgisel Bulanık WASPAS Yöntemi ile Değerlendirilmesi. İzmir İktisat Dergisi, 35(4), 777-791.
  • Yilmaz, E. A., & Hatice, C. A. N. (2018). Türkiye’nin yenilenebilir enerji potansiyeli ve gelecek hedefleri. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 8(3), 525-535.
  • Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8(3), 338-353.
  • Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika, 122(6), 3-6.

SEZGİSEL BULANIK ORTAMDA KARASAL YENİLENEBİLİR ENERJİ SANTRALİ SEÇİMİNDE TÜRKİYE ÖRNEĞİ

Yıl 2022, , 1230 - 1249, 28.12.2022
https://doi.org/10.17130/ijmeb.1133596

Öz

Enerji, küreselleşen dünyada ekonomik kalkınmanın önemli bir göstergesi olarak kabul edilmektedir ve ülkeler için hayati bir öneme sahiptir. Bir toplumda sürdürülebilir kalkınmayı sağlamak için bol enerji kaynaklarına sahip olmak gerekir. Bu enerji kaynakları makul bir maliyetle elde edilmeli ve herhangi bir olumsuz sosyal etkiye neden olmadan toplumun tüm ihtiyaçları için kullanılmalıdır. Enerji santralleri, sürekli faaliyet gösteren tüm ülkelerde elektrik üretim endüstrisinin kalbi olarak kabul edilmektedir. Sanayinin ve ekonominin ayakta kalmasında kritik ve belirleyici bir role sahip olduklarına inanılmaktadır. Enerji arzının gerekliliği ve artan talebi, daha fazla enerji santrali inşa etme ile ilgili hususlarla doğru orantılıdır. Bu nedenle, kesinlikle bir ülkedeki kalkınmanın en önemli esaslarından birisidir. Bu amaçla bu çalışmada karasal yenilenebilir enerji santrallerinin seçimi yapılmıştır. Günümüzde dünya nüfusundaki hızlı artış ve sanayileşme enerji ihtiyacını artırmaktadır. Enerji ihitiyacı genellikle fosil kaynaklı enerji kaynaklarından temin edilmektedir. Ülkemizde ve dünyada fosil kaynakların azalması ve çevreye verdikleri zarardan dolayı yenilenebilir enerji kaynaklarının önemini artırmıştır. Enerji kaynaklarının seçimi, alternatiflerin (enerji kaynağının) kriterlere göre birden çok karar verici tarafından değerlendirilmesinden ötürü bir çok kriterli grup karar verme problemi olarak görülmektedir. Bu çalışmada, karasal yenilenebilir enerji santralleri, sezgisel bulanık WASPAS yaklaşımı kullanılarak sıralanmıştır. Türkiye için en iyi karasal yenilenebilir enerji tesisleri belirlenirken ekonomik, çevresel, teknolojik ve sosyal kriterler dikkate alınmaktadır. Yapılan modelleme sonucunda güneş enerjisi santrali en uygun yenilenebilir enerji santrali olarak belirlenmiştir.

Proje Numarası

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Kaynakça

  • Adhikary, P., Roy, P. K., & Mazumdar, A. (2015). Maintenance contractor selection for small hydropower project: a fuzzy multi-criteria optimization technique approach. International Review of Mechanical Engineering, 9(2), 174-181.
  • Ahmad, S., & Tahar, R. M. (2014). Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: A case of Malaysia. Renewable energy, 63, 458-466.
  • Alizadeh, R., Soltanisehat, L., Lund, P. D., & Zamanisabzi, H. (2020). Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy, 137, 111174.
  • Amer, M., & Daim, T. U. (2011). Selection of renewable energy technologies for a developing county: a case of Pakistan. Energy for sustainable development, 15(4), 420-435.
  • Arda, Z., & Çavşi, H. (2018). Türkiye’deki jeotermal enerji santrallerinin durumu. Mühendis ve Makina, 59(691), 45-58. Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems.20(1), 87-96.
  • Balin, A., & Baraçli, H. (2017). A fuzzy multi-criteria decision making methodology based upon the interval type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey. Technological and Economic Development of Economy, 23(5), 742-763.
  • Buyukozkan, G., & Guleryuz, S. (2016). Fuzzy multi criteria decision making approach for evaluating sustainable energy technology alternatives. International journal of renewable energy sources, 1, 1-6.
  • Büyüközkan, G., & Güleryüz, S. (2016). An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. International journal of production economics, 182, 435-448.
  • Çelikbilek, Y., & Tüysüz, F. (2016). An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. Energy, 115, 1246-1258.
  • Damgaci, E., Boran, K., & Boran, F. (2017). Evaluation of Turkey's Renewable Energy Using Intuitionistic Fuzzy TOPSIS Method. Journal of polytechnic-Politeknik Dergisi
  • Erdal, L. (2012). Türkiye’de yenilenebilir enerji yatırımları ve istihdam yaratma potansiyeli. Sosyal ve Beşeri Bilimler Dergisi, 4(1), 171-181.
  • Ertay, T., Kahraman, C., & Kaya, İ. (2013). Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey. Technological and economic development of economy, 19(1), 38-62.
  • Ervural, B. C., Zaim, S., Demirel, O. F., Aydin, Z., & Delen, D. (2018). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews, 82, 1538-1550.
  • Gaoa, H., Ernesto, Y., Gonzalez, S., Zhang, W.(2020).Green supplier selection in electronics manufacturing: An approach based on consensus decision making. Journal of Cleaner Production. 245,118781. Gunter, Y. (2019). Sezgisel bulanık Kümelere Dayalı Çok Kriterli Karar Verme Yöntemleri. Yüksek Lisans Tezi, Selçuk Üniversitesi Fen Bilimleri Enstitüsü, İstatistik Anabilim Dalı.
  • Kahraman, C., Kaya, İ., & Cebi, S. (2009). A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process. Energy, 34(10), 1603-1616.
  • Katal, F., & Fazelpour, F. (2018). Multi-criteria evaluation and priority analysis of different types of existing power plants in Iran: An optimized energy planning system. Renewable Energy, 120, 163-177.
  • Lee, H. C., & Chang, C. T. (2018). Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews, 92, 883-896.
  • Memari, A., Dargi, A., Jokar, M. R. A., Ahmad, R., & Rahim, A. R. A. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of manufacturing systems, 50, 9-24.
  • Mishra, A. R., & Rani, P. (2018). Interval-valued intuitionistic fuzzy WASPAS method: Application in reservoir flood control management policy. Group Decision and Negotiation, 27(6), 1047-1078.
  • Mishra, A. R., Rani, P., Pardasani, K. R., & Mardani, A. (2019). A novel hesitant fuzzy WASPAS method for assessment of green supplier problem based on exponential information measures. Journal of Cleaner Production, 238, 117901.
  • Özkale, C., Celik, C., Turkmen, A. C., & Cakmaz, E. S. (2017). Decision analysis application intended for selection of a power plant running on renewable energy sources. Renewable and sustainable energy reviews, 70, 1011-1021.
  • Rahman, A., Farrok, O., & Haque, M. M. (2022). Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic. Renewable and Sustainable Energy Reviews, 161, 112279.
  • Sadeghi, A., Larimian, T., & Molabashi, A. (2012). Evaluation of renewable energy sources for generating electricity in province of Yazd: a fuzzy MCDM approach. Procedia-Social and Behavioral Sciences, 62, 1095-1099.
  • Štreimikienė, D., Šliogerienė, J., & Turskis, Z. (2016). Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable energy, 85, 148-156.
  • Tian, G., Zhang, H., Feng, Y., Wang, D., Peng, Y., & Jia, H. (2018). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, 81, 682-692.
  • Tirmikcioglu, N. (2021). Sezgisel Bulanık WASPAS Yöntemi ve Depo Yeri Seçimi Problemi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 21(6), 1330-1342.
  • Troldborg, M., Heslop, S., & Hough, R. L. (2014). 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, 39, 1173-1184.
  • Turgut, Z. K. (2017). Sustainable and renewable energy power palnts evaluation ve fuzzy VIKOR and fuzzy TODIM technıques. Galatasaray Üniversitesi, Fen Bilimleri Enstitüsü (Master Thesis)
  • Yazdani, M., Torkayesh, A. E., Santibanez-Gonzalez, E. D., & Otaghsara, S. K. (2020). Evaluation of renewable energy resources using integrated Shannon Entropy—EDAS model. Sustainable Operations and Computers, 1, 35-42.
  • Yildirim, B. F., & Ciftci, H. N. (2020). BIST’te İşlem Gören Tekstil Firmalarının Finansal Performanslarının Dinamik Sezgisel Bulanık WASPAS Yöntemi ile Değerlendirilmesi. İzmir İktisat Dergisi, 35(4), 777-791.
  • Yilmaz, E. A., & Hatice, C. A. N. (2018). Türkiye’nin yenilenebilir enerji potansiyeli ve gelecek hedefleri. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 8(3), 525-535.
  • Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8(3), 338-353.
  • Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika, 122(6), 3-6.
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yöneylem
Bölüm Araştırma Makaleleri
Yazarlar

Fulya Zaralı 0000-0002-7796-1040

Proje Numarası -
Yayımlanma Tarihi 28 Aralık 2022
Gönderilme Tarihi 21 Haziran 2022
Kabul Tarihi 31 Ağustos 2022
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Zaralı, F. (2022). THE SELECTION OF TERRESTRIAL RENEWABLE ENERGY POWER PLANTS IN AN INTUITIONISTIC FUZZY ENVIRONMENT: THE CASE OF TURKEY. Uluslararası Yönetim İktisat Ve İşletme Dergisi, 18(4), 1230-1249. https://doi.org/10.17130/ijmeb.1133596