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A Fuzzy Analytic Hierarchy Process Based COPRAS Approach for the Evaluation of the Renewable Energy Sources

Year 2025, Volume: 10 Issue: 1, 118 - 133, 07.03.2025

Abstract

Renewable energy sources are those that naturally replenish over time and provide an endless supply of energy without the risk of resource exhaustion. Examples include solar power, wind energy, hydropower, geothermal energy, and biomass. These energy sources are crucial due to their sustainable nature, enabling continuous energy production while minimizing environmental harm and preserving natural resources. Unlike conventional fossil fuels, which are limited and heavily pollute the environment, renewable energy significantly reduces carbon emissions, improves air quality, and helps address climate change challenges. Embracing renewable energy is vital for building a sustainable future. This study evaluates renewable energy sources using a hybrid fuzzy multi-criteria decision-making approach. The proposed method integrates two techniques: the fuzzy analytic hierarchy process and the fuzzy-based COPRAS method. The fuzzy analytic hierarchy process is first applied to determine the relative importance of criteria and create a fuzzy decision matrix. Then, the COPRAS method processes this matrix, incorporating the calculated weights, to systematically assess and rank renewable energy options.

References

  • Barry, M. L., Steyn, H., and Brent, A. (2011). Selection of renewable energy technologies for Africa: Eight case studies in Rwanda, Tanzania and Malawi. Renewable Energy, 36(11), 2845-2852.
  • Bohra, S. S., and Anvari‐Moghaddam, A. (2022). A comprehensive review on applications of multicriteria decision‐making methods in power and energy systems. International Journal of Energy Research, 46(4), 4088-4118.
  • Bundschuh, J., Kaczmarczyk, M., Ghaffour, N., and Tomaszewska, B. (2021). State-of-the-art of renewable energy sources used in water desalination: Present and future prospects. Desalination, 508, 115035.
  • Celikbilek, Y., Adıgüzel Tüylü, A. N., and Esnaf, Ş. (2016). Industrial coffee machine selection with the Fuzzy analytic hierarchy process. International Journal of Management and Applied Science, 2(2), 20-23.
  • Doukas, H., Karakosta, C., and Psarras, J. (2010). Computing with words to assess the sustainability of renewable energy options. Expert Systems with Applications, 37(7), 5491-5497.
  • Ilbahar, E., Cebi, S., and Kahraman, C. (2020). Prioritization of renewable energy sources using multi-experts Pythagorean fuzzy WASPAS. Journal of Intelligent and Fuzzy Systems, 39(5), 6407-6417.
  • Kabeyi, M. J. B., and Olanrewaju, O. A. (2022). Geothermal wellhead technology power plants in grid electricity generation: A review. Energy Strategy Reviews, 39, 100735.
  • Kahraman, C., Kaya, İ., and 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.
  • Kolamroudi, M. K., Ilkan, M., Egelioglu, F., and Safaei, B. (2022). Maximization of the output power of low concentrating photovoltaic systems by the application of reflecting mirrors. Renewable Energy, 189, 822-835.
  • Kaya, T., and Kahraman, C. (2010). Multicriteria renewable energy planning using an integrated fuzzy VIKOR and AHP methodology: The case of Istanbul. Energy, 35(6), 2517-2527.
  • Kebede, A. A., Kalogiannis, T., Van Mierlo, J., and Berecibar, M. (2022). A comprehensive review of stationary energy storage devices for large scale renewable energy sources grid integration. Renewable and Sustainable Energy Reviews, 159, 112213.
  • Kim, J., Ryu, D., and Sovacool, B. K. (2021). Critically assessing and projecting the frequency, severity, and cost of major energy accidents. The Extractive Industries and Society, 8(2), 100885.
  • Lenz, V., and Ortwein, A. (2017). SmartBiomassHeat–heat from solid biofuels as an integral part of a future energy system based on renewables. Chemical Engineering and Technology, 40(2), 313-322.

Yenilenebilir Enerji Kaynaklarının Değerlendirilmesi için Bulanık Analitik Hiyerarşi Süreci Tabanlı COPRAS Yaklaşımı

Year 2025, Volume: 10 Issue: 1, 118 - 133, 07.03.2025

Abstract

Yenilenebilir enerji kaynakları, doğal olarak zamanla kendini yenileyen ve tükenme riski olmadan sınırsız enerji sağlayan kaynaklardır. Örnekler arasında güneş enerjisi, rüzgar enerjisi, hidroelektrik enerji, jeotermal enerji ve biyokütle bulunur. Bu enerji kaynakları, sürdürülebilir yapıları sayesinde sürekli enerji üretimini mümkün kılar ve çevresel zararları en aza indirirken doğal kaynakların korunmasına yardımcı olur. Geleneksel fosil yakıtların aksine, yenilenebilir enerji karbon emisyonlarını önemli ölçüde azaltır, hava kalitesini iyileştirir ve iklim değişikliğiyle ilgili zorlukların üstesinden gelinmesine yardımcı olur. Yenilenebilir enerjiye yönelmek, sürdürülebilir bir gelecek inşa etmek için hayati önem taşımaktadır. Bu çalışma, yenilenebilir enerji kaynaklarını hibrit bir bulanık çok kriterli karar verme yaklaşımı kullanarak değerlendirmektedir. Önerilen yöntem, iki tekniği birleştirmektedir: bulanık analitik hiyerarşi süreci ve bulanık temelli COPRAS yöntemi. İlk olarak, bulanık analitik hiyerarşi süreci, kriterlerin göreceli önemini belirlemek ve bulanık bir karar matrisi oluşturmak için uygulanmıştır. Ardından COPRAS yöntemi, hesaplanan ağırlıkları içeren bu matrisi işleyerek yenilenebilir enerji seçeneklerini sistematik bir şekilde değerlendirmiş ve sıralamıştır.

References

  • Barry, M. L., Steyn, H., and Brent, A. (2011). Selection of renewable energy technologies for Africa: Eight case studies in Rwanda, Tanzania and Malawi. Renewable Energy, 36(11), 2845-2852.
  • Bohra, S. S., and Anvari‐Moghaddam, A. (2022). A comprehensive review on applications of multicriteria decision‐making methods in power and energy systems. International Journal of Energy Research, 46(4), 4088-4118.
  • Bundschuh, J., Kaczmarczyk, M., Ghaffour, N., and Tomaszewska, B. (2021). State-of-the-art of renewable energy sources used in water desalination: Present and future prospects. Desalination, 508, 115035.
  • Celikbilek, Y., Adıgüzel Tüylü, A. N., and Esnaf, Ş. (2016). Industrial coffee machine selection with the Fuzzy analytic hierarchy process. International Journal of Management and Applied Science, 2(2), 20-23.
  • Doukas, H., Karakosta, C., and Psarras, J. (2010). Computing with words to assess the sustainability of renewable energy options. Expert Systems with Applications, 37(7), 5491-5497.
  • Ilbahar, E., Cebi, S., and Kahraman, C. (2020). Prioritization of renewable energy sources using multi-experts Pythagorean fuzzy WASPAS. Journal of Intelligent and Fuzzy Systems, 39(5), 6407-6417.
  • Kabeyi, M. J. B., and Olanrewaju, O. A. (2022). Geothermal wellhead technology power plants in grid electricity generation: A review. Energy Strategy Reviews, 39, 100735.
  • Kahraman, C., Kaya, İ., and 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.
  • Kolamroudi, M. K., Ilkan, M., Egelioglu, F., and Safaei, B. (2022). Maximization of the output power of low concentrating photovoltaic systems by the application of reflecting mirrors. Renewable Energy, 189, 822-835.
  • Kaya, T., and Kahraman, C. (2010). Multicriteria renewable energy planning using an integrated fuzzy VIKOR and AHP methodology: The case of Istanbul. Energy, 35(6), 2517-2527.
  • Kebede, A. A., Kalogiannis, T., Van Mierlo, J., and Berecibar, M. (2022). A comprehensive review of stationary energy storage devices for large scale renewable energy sources grid integration. Renewable and Sustainable Energy Reviews, 159, 112213.
  • Kim, J., Ryu, D., and Sovacool, B. K. (2021). Critically assessing and projecting the frequency, severity, and cost of major energy accidents. The Extractive Industries and Society, 8(2), 100885.
  • Lenz, V., and Ortwein, A. (2017). SmartBiomassHeat–heat from solid biofuels as an integral part of a future energy system based on renewables. Chemical Engineering and Technology, 40(2), 313-322.
There are 13 citations in total.

Details

Primary Language English
Subjects Planning and Decision Making, Natural Resources Economy
Journal Section Articles
Authors

Yakup Çelikbilek 0000-0003-0585-1085

Publication Date March 7, 2025
Submission Date February 1, 2025
Acceptance Date February 24, 2025
Published in Issue Year 2025 Volume: 10 Issue: 1

Cite

APA Çelikbilek, Y. (2025). A Fuzzy Analytic Hierarchy Process Based COPRAS Approach for the Evaluation of the Renewable Energy Sources. The Journal of International Scientific Researches, 10(1), 118-133.