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A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey

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  • Ibrahim Yilmaz

    (Department of Industrial Engineering, School of Engineering and Natural Sciences, Ankara Yıldırım Beyazıt University (AYBU), Ankara 06010, Turkey)

Abstract

The production of renewable energy is becoming one of the most important issues for communities due to the increasing energy demand. The purpose of this paper is to develop a systematized, sustainability-focused evaluation framework for determining the efficiency of wind farms in Turkey. The environmental impact and long-term viability of wind farms are evaluated using an evaluation framework centered on sustainability. The evaluation of their sustainability involves analyzing their energy production, environmental impacts and economic viability. In this study, DEA–Fuzzy COPRAS aims to evaluate the efficiency of 11 wind power plants located in Turkey in the Marmara Region. As inputs, the number of wind turbines, investment cost and distance from the grid are selected. As output, electricity is produced, and daily production time is considered. The proposed DEA–Fuzzy COPRAS aims to eliminate the disadvantages of the conventional methods and to be able to make better decisions regarding the weight value under uncertain conditions. The main advantages of the proposed DEA–Fuzzy COPRAS include a more accurate evaluation of efficiency and the ability to consider multiple criteria simultaneously. Additionally, the proposed DEA–Fuzzy COPRAS considers uncertainty in the inputs and outputs of wind energy production. The results of the proposed work are validated by comparing them with those obtained from a sensitivity analysis of the criteria. Therefore, decision makers can evaluate the efficiency of wind power plants accurately under an imprecise environment. Wind power plant managers or investors and other renewable energy projects can benefit from the proposed method’s implementation by allowing governments and stakeholders to save money and make better use of resources during the planning phase.

Suggested Citation

  • Ibrahim Yilmaz, 2023. "A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11267-:d:1197732
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    1. Azadeh, A. & Sheikhalishahi, M. & Asadzadeh, S.M., 2011. "A flexible neural network-fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity," Renewable Energy, Elsevier, vol. 36(12), pages 3394-3401.
    2. Ederer, Nikolaus, 2015. "The market value and impact of offshore wind on the electricity spot market: Evidence from Germany," Applied Energy, Elsevier, vol. 154(C), pages 805-814.
    3. Javed, Muhammad Shahzad & Ma, Tao & Jurasz, Jakub & Canales, Fausto A. & Lin, Shaoquan & Ahmed, Salman & Zhang, Yijie, 2021. "Economic analysis and optimization of a renewable energy based power supply system with different energy storages for a remote island," Renewable Energy, Elsevier, vol. 164(C), pages 1376-1394.
    4. Tao Xu & Jianxin You & Hui Li & Luning Shao, 2020. "Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review," Energies, MDPI, vol. 13(14), pages 1-20, July.
    5. Papież, Monika & Śmiech, Sławomir & Frodyma, Katarzyna, 2019. "Factors affecting the efficiency of wind power in the European Union countries," Energy Policy, Elsevier, vol. 132(C), pages 965-977.
    6. Li, Jiaxin & Wang, Zihan & Cheng, Xin & Shuai, Jing & Shuai, Chuanmin & Liu, Jing, 2020. "Has solar PV achieved the national poverty alleviation goals? Empirical evidence from the performances of 52 villages in rural China," Energy, Elsevier, vol. 201(C).
    7. Akbari, Negar & Jones, Dylan & Treloar, Richard, 2020. "A cross-European efficiency assessment of offshore wind farms: A DEA approach," Renewable Energy, Elsevier, vol. 151(C), pages 1186-1195.
    8. Min-Chun Yu & Min-Hong Su, 2017. "Using Fuzzy DEA for Green Suppliers Selection Considering Carbon Footprints," Sustainability, MDPI, vol. 9(4), pages 1-11, March.
    9. Iribarren, Diego & Martín-Gamboa, Mario & Dufour, Javier, 2013. "Environmental benchmarking of wind farms according to their operational performance," Energy, Elsevier, vol. 61(C), pages 589-597.
    10. Imane Tronnebati & Manal El Yadari & Fouad Jawab, 2022. "A Review of Green Supplier Evaluation and Selection Issues Using MCDM, MP and AI Models," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
    11. Mohamed Abdel-Basset & Abduallah Gamal & Ripon K. Chakrabortty & Michael Ryan & Nissreen El-Saber, 2021. "A Comprehensive Framework for Evaluating Sustainable Green Building Indicators under an Uncertain Environment," Sustainability, MDPI, vol. 13(11), pages 1-25, June.
    12. Iglesias, Guillermo & Castellanos, Pablo & Seijas, Amparo, 2010. "Measurement of productive efficiency with frontier methods: A case study for wind farms," Energy Economics, Elsevier, vol. 32(5), pages 1199-1208, September.
    13. Zhao, Jin & Patwary, Ataul Karim & Qayyum, Abdul & Alharthi, Majed & Bashir, Furrukh & Mohsin, Muhammad & Hanif, Imran & Abbas, Qaiser, 2022. "The determinants of renewable energy sources for the fueling of green and sustainable economy," Energy, Elsevier, vol. 238(PC).
    14. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    15. Dario Maradin & Bojana Olgić Draženović & Saša Čegar, 2023. "The Efficiency of Offshore Wind Energy Companies in the European Countries: A DEA Approach," Energies, MDPI, vol. 16(9), pages 1-16, April.
    16. Iribarren, Diego & Vázquez-Rowe, Ian & Rugani, Benedetto & Benetto, Enrico, 2014. "On the feasibility of using emergy analysis as a source of benchmarking criteria through data envelopment analysis: A case study for wind energy," Energy, Elsevier, vol. 67(C), pages 527-537.
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