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Applying a Combination of AHP, ANP, and PROMETHEE Methods to Find the Optimal Location for Solar Power Plant

Year 2021, Issue: 32, 1076 - 1085, 31.12.2021
https://doi.org/10.31590/ejosat.1039961

Abstract

One of the well-known renewable energy resources is solar energy which has been developed rapidly in recent years. Turkey is one of the high energy consumer countries where has a good potential for using solar power due to its geographical location. Choosing the right location is one of the main issues related to the solar power plant problem. The main objective of this study is to select the optimal location to install a solar power plant among the five cities (Antalya, Nigde, Konya, Mersin, and Isparta) in the south of Turkey, which all of them are considered as potential locations because of receiving a high amount of solar radiation. To accomplish this task, three well-known multi-criteria decision-making methods (AHP, ANP, and PROMETHEE) are used to find the best location considering six different criteria. To simplify and improve the accuracy of calculation, SuperDecisions and VisualPROMETHEE Programs are utilized for analyzing the data. The program results show that Mersin is selected as the best location and the second one is Antalya. Besides, the lowest scored city is Nigde which is considered as the least preferred alternative.

References

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AHP, ANP ve PROMETHEE Yöntemlerinin Bir Kombinasyonunun Uygulanması, Güneş Enerjili Elektrik Santrali için En Uygun Yerin Bulunması

Year 2021, Issue: 32, 1076 - 1085, 31.12.2021
https://doi.org/10.31590/ejosat.1039961

Abstract

Güneş enerjisi, son yıllarda hızla gelişen popüler yenilenebilir enerji kaynaklarından biridir. Türkiye, coğrafi konumu nedeniyle güneş enerjisini kullanma potansiyeli ve enerji tüketimi yüksek ülkelerden biridir. Güneş enerjili elektrik santrali sorunu ile ilgili temel konulardan biri doğru yer seci midir. Bu çalışma, Türkiye'nin güneyindeki beş şehir (Antalya, Mersin, Niğde, Isparta ve Konya) arasından , çoğunun iyi bir oranda güneş radyasyonu aldığı, güneş enerjili elektrik santrali kurmak için en uygun yeri seçmeyi amaçlamaktadır. Bu görevi gerçekleştirmek için, altı farklı kriteri göz önünde bulundurarak en iyi konumu bulmak için iyi bilinen üç çok kriterli karar verme yöntemi (AHP, ANP ve PROMETHEE) kullanılır. Hesaplamanın doğruluğunu basitleştirmek ve geliştirmek için, verilerin analizinde SuperDecisions ve VisualPROMETHEE Programları kullanılmaktadır. Çalışmanın sonuçları, Mersin'in ardından Antalya'nin en iyi alternatif olduğunu göstermektedir, Niğde ise en az tercih edilen alternatif olarak değerlendirilmek üzere en düşük puanı almıştır.

References

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  • Al Garni, H. Z., & Awasthi, A. (2017). Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia. Applied Energy, 206(July), Energy Report of Turkeyhttps://doi.org/10.1016/j.apenergy.2017.10.024
  • Albadvi, A., Chaharsooghi, S. K., & Esfahanipour, A. (2006). Decision making in stock trading: An application of PROMETHEE. European Journal of Operational Research, 177(2), 673–683. https://doi.org/10.1016/j.ejor.2005.11.022
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  • Chung, S. H., Lee, A. H. I., & Pearn, W. L. (2005). Analytic network process (ANP) approach for product mix planning in semiconductor fabricator. International Journal of Production Economics, 96(1), 15–36. https://doi.org/10.1016/j.ijpe.2004.02.006
  • Colak, H. E., Memisoglu, T., & Gercek, Y. (2020a). Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey. Renewable Energy, 149, 565–576. https://doi.org/10.1016/j.renene.2019.12.078
  • Colak, H. E., Memisoglu, T., & Gercek, Y. (2020b). Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey. Renewable Energy, 149, 565–576. https://doi.org/10.1016/j.renene.2019.12.078
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  • De Smet, Y., & Guzmán, L. M. (2004). Towards multicriteria clustering: An extension of the k-means algorithm. European Journal of Operational Research, 158(2), 390–398. https://doi.org/10.1016/j.ejor.2003.06.012
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  • Doumpos, M., & Zopounidis, C. (2004). A multicriteria classification approach based on pairwise comparisons. European Journal of Operational Research, 158(2), 378–389. https://doi.org/10.1016/j.ejor.2003.06.011
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  • Erdoĝan, M., & Kaya, I. (2015). An integrated multi-criteria decision-making methodology based on type-2 fuzzy sets for selection among energy alternatives in Turkey. Iranian Journal of Fuzzy Systems, 12(1), 1–25. https://doi.org/10.22111/ijfs.2015.1839
  • Finance BNE. (2018). Global Trends in Renewable Energy Investment Report.
  • Fontana, M. E., & Morais, D. C. (2016). Decision model to control water losses in distribution networks. Producao, 26(4), 688–697. https://doi.org/10.1590/0103-6513.201815
  • GEÇEN, R. (2019). Determining the potential of solar power and suitable area for constructing solar power plant in hatay province. Turkish Studies-Social Sciences, Volume 14(Volume 14 Issue 6), 3031–3054. https://doi.org/10.29228/turkishstudies.30212
  • Hajkowicz, S., & Higgins, A. (2008). A comparison of multiple criteria analysis techniques for water resource management. European Journal of Operational Research, 184(1), 255–265. https://doi.org/10.1016/j.ejor.2006.10.045
  • Hasan, D., Ümit, H., & Serhat, Y. (2016). Performance Assessment of Deposit Banks with CAMELS Analysis using Fuzzy ANP-MOORA Approaches and an Application on Turkish Banking Sector. Asian Journal of Research in Business Economics and Management, 6(2), 32. https://doi.org/10.5958/2249-7307.2016.00009.8
  • Hosseini, L., Tavakkoli-Moghaddam, R., Vahdani, B., Mousavi, S. M., & Kia, R. (2013). Using the Analytical Network Process to Select the Best Strategy for Reducing Risks in a Supply Chain. Journal of Engineering (United Kingdom), 2013. https://doi.org/10.1155/2013/375628
  • Hyde, K. M., & Maier, H. R. (2006). Distance-based and stochastic uncertainty analysis for multi-criteria decision analysis in Excel using Visual Basic for Applications. Environmental Modelling and Software, 21(12), 1695–1710. https://doi.org/10.1016/j.envsoft.2005.08.004
  • Jung, J., Han, S., & Kim, B. (2019). Digital numerical map-oriented estimation of solar energy potential for site selection of photovoltaic solar panels on national highway slopes. Applied Energy, 242, 57–68. https://doi.org/10.1016/j.apenergy.2019.03.101
  • Ka, B. (2011). Application of Fuzzy AHP and ELECTRE to China Dry Port Location Selection. The Asian Journal of Shipping and Logistics, 27(2), 331–353. https://doi.org/10.1016/S2092-5212(11)80015-5
  • Kalogeras, N., Baourakis, G., Zopounidis, C., & Van Dijk, G. (2005). Evaluating the financial performance of agri-food firms: A multicriteria decision-aid approach. Journal of Food Engineering, 70(3), 365–371. https://doi.org/10.1016/j.jfoodeng.2004.01.039
  • Kang, H. Y., & Lee, A. H. I. (2007). Priority mix planning for semiconductor fabrication by fuzzy AHP ranking. Expert Systems with Applications, 32(2), 560–570. https://doi.org/10.1016/j.eswa.2006.01.035
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  • Leung, L. C., & Cao, D. (2000). On consistency and ranking of alternatives in fuzzy AHP. European Journal of Operational Research, 124(1), 102–113. https://doi.org/10.1016/S0377-2217(99)00118-6
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There are 58 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Nıma Mırzaeı 0000-0002-8585-8713

Raheleh Nowzari 0000-0001-6601-4235

Publication Date December 31, 2021
Published in Issue Year 2021 Issue: 32

Cite

APA Mırzaeı, N., & Nowzari, R. (2021). Applying a Combination of AHP, ANP, and PROMETHEE Methods to Find the Optimal Location for Solar Power Plant. Avrupa Bilim Ve Teknoloji Dergisi(32), 1076-1085. https://doi.org/10.31590/ejosat.1039961