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Yenilenebilir Enerji Kaynaklarının Belirsizlik Altında Değerlendirilmesi İçin Bir Hibrit Çok Kriterli Analiz Yaklaşımı

Year 2017, , 317 - 328, 11.12.2017
https://doi.org/10.17093/alphanumeric.359662

Abstract

Yenilenebilir enerji kaynaklarının değerlendirilmesi, birden çok kriterin dikkate alınması ve bir araya getirilmesi ile bunlarla ilgili uygun verilerin kullanılmasını gerektiren kritik ve karmaşık bir süreçtir. Bu çalışma, yenilenebilir enerji alternatiflerinin genel değerlendirmesi için bir simülasyon tabanlı çok kriterli karar modeli sunmaktadır. Bu model verilerdeki belirsizlik ve değişkenliği daha iyi temsil edebilmek için Monte Carlo simülasyon tekniğini Gri İlişkisel Analiz (GİA) yöntemiyle bütünleştirmektedir. Simülasyon tabanlı GİA yöntemi, yenilenebilir enerji alternatifleri olan güneş, rüzgar, hidroelektrik, biyokütle ve jeotermal enerjinin sıralamasında kullanılmaktadır. Önerilen modelin etkinliği ve uygulanabilirliği, 5 yenilenebilir enerji alternatifinin 12 kritere göre değerlendirildiği bir uygulama ile de gösterilmektedir.

References

  • Ahmad, S., & Tahar, R. M.,”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, 2014.
  • Applied Energy Studies, The environmental cost of energy. Damascus. 2010.
  • Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J. P., & Pla-Rubio, A.,”An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects”. Energy, 66, 222-238, 2014.
  • Arce, M. E., Saavedra, Á., Míguez, J. L., & Granada, E., “The use of grey-based methods in multi-criteria decision analysis for the evaluation of sustainable energy systems: A review”. Renewable and Sustainable Energy Reviews, 47, 924-932, 2015.
  • Atmaca, E., & Basar, H. B., “Evaluation of power plants in Turkey using Analytic Network Process (ANP)”. Energy, 44(1), 555-563, 2012.
  • Aydin, N. Y., Kentel, E., & Duzgun, H. S., “GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey”. Energy Conversion and Management, 70, 90-106, 2013.
  • Banos, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J.,”Optimization methods applied to renewable and sustainable energy: A review”. Renewable and Sustainable Energy Reviews, 15(4), 1753-1766, 2011.
  • Beccali, M., Cellura, M., & Mistretta, M., “Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology”. Renewable energy, 28(13), 2063-2087, 2003.
  • Bhowmik, C., Bhowmik, S., Ray, A., & Pandey, K. M., “Optimal green energy planning for sustainable development: A review”. Renewable and Sustainable Energy Reviews. 71, 796-813, 2017.
  • Bloomberg, Renewable Energy Power of Turkey. 2014, http://awsassets.wwftr.panda.org/downloads/wwf_turkiye_turkiye_nin_yenilenebilir_gucu_raporu_1.pdf Access Date: 15.02.2017.
  • Chan, J. W., & Tong, T. K., “Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach”. Materials & Design, 28(5), 1539-1546, 2007.
  • Chen, W., & Zou, Y., “An integrated method for supplier selection from the perspective of risk aversion”. Applied Soft Computing, 54, 449-455, 2016.
  • Çelikbilek, Y., & Tüysüz, F., “An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources”. Energy, 115, 1246-1258, 2016.
  • Dağdeviren, M., & Eraslan, E., “Priority determination in strategic energy policies in Turkey using analytic network process (ANP) with group decision making”. International Journal of Energy Research, 32(11), 1047-1057, 2008.
  • Deng, J. L., “Control problems of grey systems”. Systems & Control Letters, 1 (5), 288-294, 1982.
  • Doukas, H., Karakosta, C., & Psarras, J., “Computing with words to assess the sustainability of renewable energy options”. Expert Systems with Applications, 37(7), 5491-5497, 2010.
  • Edenhofer, O., Madruga, R. P., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., ... & Stechow, C. V., “Renewable energy sources and climate change mitigation: summary for policymakers and technical summary”. Special report of the intergovernmental panel on climate change, Cambridge University Press, New York, 2012.
  • EU Commission.”World energy, technology and climate policy outlook 2030”. Energy, environment and sustainable development programme, European Commission’s Directorate-General for Research, Brussels, 2003.
  • Fthenakis, V., & Kim, H. C., “Land use and electricity generation: A life-cycle analysis”. Renewable and Sustainable Energy Reviews, 13(6), 1465-1474, 2009.
  • Georgopoulou, E., Lalas, D., & Papagiannakis, L., “A multicriteria decision aid approach for energy planning problems: the case of renewable energy option”. European Journal of Operational Research, 103(1), 38-54, 1997.
  • Golmohammadi, D., & Mellat-Parast, M., “Developing a grey-based decision-making model for supplier selection”. International Journal of Production Economics, 137(2), 191-200, 2012.
  • Goumas, M., & Lygerou, V., “An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects”. European Journal of Operational Research, 123(3), 606-613, 2000.
  • Greenpeace, Energy Revolution Report 2015. http://www.greenpeace.org/turkey/tr/news/enerji-devrimi-raporu-yayimlandi-010715/ Access Date: 15.02.2017.
  • Hämäläinen, R. P., & Karjalainen, R., “Decision support for risk analysis in energy policy”. European Journal of Operational Research, 56(2), 172-183, 1992.
  • Haralambopoulos, D. A., & Polatidis, H., “Renewable energy projects: structuring a multi-criteria group decision-making framework”. Renewable energy, 28(6), 961-973, 2003.
  • Hashemi, S. H., Karimi, A., & Tavana, M., “An integrated green supplier selection approach with analytic network process and improved Grey relational analysis”. International Journal of Production Economics, 159, 178-191, 2015.
  • Huang, S. J., Chiu, N. H., & Chen, L. W., “Integration of the grey relational analysis with genetic algorithm for software effort estimation”. European Journal of Operational Research, 188(3), 898-909, 2008.
  • Kaya, T., & Kahraman, C., “Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul”. Energy, 35(6), 2517-2527, 2010.
  • Lee, A. H., Chen, H. H., & Kang, H. Y., “Multi-criteria decision making on strategic selection of wind farms”. Renewable Energy, 34(1), 120-126, 2009.
  • Lee, W. S., & Lin, Y. C., “Evaluating and ranking energy performance of office buildings using Grey relational analysis”. Energy, 36(5), 2551-2556, 2011.
  • Li-bo, Z., & Tao, Y., “The evaluation and selection of renewable energy technologies in China”. Energy Procedia, 61, 2554-2557, 2014.
  • Ministry of Energy and Natural Resources, World and our country the appearance of energy and natural resources Report, 2016, http://www.enerji.gov.tr/File/?path=ROOT%2f1%2fDocuments%2fEnerji%20ve%20Tabii%20Kaynaklar%20G%C3%B6r%C3%BCn%C3%BCm%C3%BC%2fSayi_14.pdf. Access Date: 15.02.2017.
  • Papadopoulos, A., & Karagiannidis, A., “Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems”. Omega, 36(5), 766-776, 2008.
  • Samvedi, A., Jain, V., & Chan, F. T., “An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis”. International Journal of Production Research, 50(12), 3211-3221, 2012.
  • San Cristóbal, J. R., “Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method”. Renewable energy, 36(2), 498-502, 2011.
  • Štreimikienė, D., Šliogerienė, J., & Turskis, Z., “Multi-criteria analysis of electricity generation technologies in Lithuania”. Renewable Energy, 85, 148-156, 2016.
  • Şengül, Ü., Eren, M., Shiraz, S. E., Gezder, V., & Şengül, A. B., “Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey”. Renewable Energy, 75, 617-625, 2015.
  • Tasri, A., & Susilawati, A., “Selection among renewable energy alternatives based on a fuzzy analytic hierarchy process in Indonesia”. Sustainable Energy Technologies and Assessments, 7, 34-44, 2014.
  • Topcu, Y. I., & Ulengin, F., “Energy for the future: An integrated decision aid for the case of Turkey”. Energy, 29(1), 137-154, 2004.
  • Ulutaş, B. H.,”Determination of the appropriate energy policy for Turkey”. Energy, 30(7), 1146-1161, 2005. US Energy Information Administration, Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2014. Washington DC, 2014
  • Uyan, M., “GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/Turkey”. Renewable and Sustainable Energy Reviews, 28, 11-17, 2013.
  • Wang, B., Kocaoglu, D. F., Daim, T. U., & Yang, J., “A decision model for energy resource selection in China”. Energy Policy, 38(11), 7130-7141, 2010.
  • Yang, C. C., & Chen, B. S., “Supplier selection using combined analytical hierarchy process and grey relational analysis”. Journal of Manufacturing Technology Management, 17(7), 926-941, 2006.
  • Zhang, S. F., & Liu, S. Y., “A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection”. Expert Systems with Applications, 38(9), 11401-11405, 2011.

A Hybrid Multi-Criteria Analysis Approach for the Assessment of Renewable Energy Resources Under Uncertainty

Year 2017, , 317 - 328, 11.12.2017
https://doi.org/10.17093/alphanumeric.359662

Abstract

Evaluation of renewable energy resources is a critical and complex process which requires the assessment and aggregation of multiple criteria and also the usage of appropriate data related to them. This study presents a simulation based multi-criteria model for the general evaluation of renewable energy alternatives. This model integrates Monte Carlo simulation technique with Grey Relational Analysis (GRA) method to be able to represent the variability and the uncertainty inherent in the data. Simulation based GRA method is used for ranking the renewable energy alternatives which are solar, wind, hydroelectric, biomass and geothermal energy. The effectiveness and the applicability of the proposed model is also illustrated with an application in which 5 renewable energy alternatives are evaluated according to 12 criteria.

References

  • Ahmad, S., & Tahar, R. M.,”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, 2014.
  • Applied Energy Studies, The environmental cost of energy. Damascus. 2010.
  • Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J. P., & Pla-Rubio, A.,”An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects”. Energy, 66, 222-238, 2014.
  • Arce, M. E., Saavedra, Á., Míguez, J. L., & Granada, E., “The use of grey-based methods in multi-criteria decision analysis for the evaluation of sustainable energy systems: A review”. Renewable and Sustainable Energy Reviews, 47, 924-932, 2015.
  • Atmaca, E., & Basar, H. B., “Evaluation of power plants in Turkey using Analytic Network Process (ANP)”. Energy, 44(1), 555-563, 2012.
  • Aydin, N. Y., Kentel, E., & Duzgun, H. S., “GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey”. Energy Conversion and Management, 70, 90-106, 2013.
  • Banos, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J.,”Optimization methods applied to renewable and sustainable energy: A review”. Renewable and Sustainable Energy Reviews, 15(4), 1753-1766, 2011.
  • Beccali, M., Cellura, M., & Mistretta, M., “Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology”. Renewable energy, 28(13), 2063-2087, 2003.
  • Bhowmik, C., Bhowmik, S., Ray, A., & Pandey, K. M., “Optimal green energy planning for sustainable development: A review”. Renewable and Sustainable Energy Reviews. 71, 796-813, 2017.
  • Bloomberg, Renewable Energy Power of Turkey. 2014, http://awsassets.wwftr.panda.org/downloads/wwf_turkiye_turkiye_nin_yenilenebilir_gucu_raporu_1.pdf Access Date: 15.02.2017.
  • Chan, J. W., & Tong, T. K., “Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach”. Materials & Design, 28(5), 1539-1546, 2007.
  • Chen, W., & Zou, Y., “An integrated method for supplier selection from the perspective of risk aversion”. Applied Soft Computing, 54, 449-455, 2016.
  • Çelikbilek, Y., & Tüysüz, F., “An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources”. Energy, 115, 1246-1258, 2016.
  • Dağdeviren, M., & Eraslan, E., “Priority determination in strategic energy policies in Turkey using analytic network process (ANP) with group decision making”. International Journal of Energy Research, 32(11), 1047-1057, 2008.
  • Deng, J. L., “Control problems of grey systems”. Systems & Control Letters, 1 (5), 288-294, 1982.
  • Doukas, H., Karakosta, C., & Psarras, J., “Computing with words to assess the sustainability of renewable energy options”. Expert Systems with Applications, 37(7), 5491-5497, 2010.
  • Edenhofer, O., Madruga, R. P., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., ... & Stechow, C. V., “Renewable energy sources and climate change mitigation: summary for policymakers and technical summary”. Special report of the intergovernmental panel on climate change, Cambridge University Press, New York, 2012.
  • EU Commission.”World energy, technology and climate policy outlook 2030”. Energy, environment and sustainable development programme, European Commission’s Directorate-General for Research, Brussels, 2003.
  • Fthenakis, V., & Kim, H. C., “Land use and electricity generation: A life-cycle analysis”. Renewable and Sustainable Energy Reviews, 13(6), 1465-1474, 2009.
  • Georgopoulou, E., Lalas, D., & Papagiannakis, L., “A multicriteria decision aid approach for energy planning problems: the case of renewable energy option”. European Journal of Operational Research, 103(1), 38-54, 1997.
  • Golmohammadi, D., & Mellat-Parast, M., “Developing a grey-based decision-making model for supplier selection”. International Journal of Production Economics, 137(2), 191-200, 2012.
  • Goumas, M., & Lygerou, V., “An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects”. European Journal of Operational Research, 123(3), 606-613, 2000.
  • Greenpeace, Energy Revolution Report 2015. http://www.greenpeace.org/turkey/tr/news/enerji-devrimi-raporu-yayimlandi-010715/ Access Date: 15.02.2017.
  • Hämäläinen, R. P., & Karjalainen, R., “Decision support for risk analysis in energy policy”. European Journal of Operational Research, 56(2), 172-183, 1992.
  • Haralambopoulos, D. A., & Polatidis, H., “Renewable energy projects: structuring a multi-criteria group decision-making framework”. Renewable energy, 28(6), 961-973, 2003.
  • Hashemi, S. H., Karimi, A., & Tavana, M., “An integrated green supplier selection approach with analytic network process and improved Grey relational analysis”. International Journal of Production Economics, 159, 178-191, 2015.
  • Huang, S. J., Chiu, N. H., & Chen, L. W., “Integration of the grey relational analysis with genetic algorithm for software effort estimation”. European Journal of Operational Research, 188(3), 898-909, 2008.
  • Kaya, T., & Kahraman, C., “Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul”. Energy, 35(6), 2517-2527, 2010.
  • Lee, A. H., Chen, H. H., & Kang, H. Y., “Multi-criteria decision making on strategic selection of wind farms”. Renewable Energy, 34(1), 120-126, 2009.
  • Lee, W. S., & Lin, Y. C., “Evaluating and ranking energy performance of office buildings using Grey relational analysis”. Energy, 36(5), 2551-2556, 2011.
  • Li-bo, Z., & Tao, Y., “The evaluation and selection of renewable energy technologies in China”. Energy Procedia, 61, 2554-2557, 2014.
  • Ministry of Energy and Natural Resources, World and our country the appearance of energy and natural resources Report, 2016, http://www.enerji.gov.tr/File/?path=ROOT%2f1%2fDocuments%2fEnerji%20ve%20Tabii%20Kaynaklar%20G%C3%B6r%C3%BCn%C3%BCm%C3%BC%2fSayi_14.pdf. Access Date: 15.02.2017.
  • Papadopoulos, A., & Karagiannidis, A., “Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems”. Omega, 36(5), 766-776, 2008.
  • Samvedi, A., Jain, V., & Chan, F. T., “An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis”. International Journal of Production Research, 50(12), 3211-3221, 2012.
  • San Cristóbal, J. R., “Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method”. Renewable energy, 36(2), 498-502, 2011.
  • Štreimikienė, D., Šliogerienė, J., & Turskis, Z., “Multi-criteria analysis of electricity generation technologies in Lithuania”. Renewable Energy, 85, 148-156, 2016.
  • Şengül, Ü., Eren, M., Shiraz, S. E., Gezder, V., & Şengül, A. B., “Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey”. Renewable Energy, 75, 617-625, 2015.
  • Tasri, A., & Susilawati, A., “Selection among renewable energy alternatives based on a fuzzy analytic hierarchy process in Indonesia”. Sustainable Energy Technologies and Assessments, 7, 34-44, 2014.
  • Topcu, Y. I., & Ulengin, F., “Energy for the future: An integrated decision aid for the case of Turkey”. Energy, 29(1), 137-154, 2004.
  • Ulutaş, B. H.,”Determination of the appropriate energy policy for Turkey”. Energy, 30(7), 1146-1161, 2005. US Energy Information Administration, Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2014. Washington DC, 2014
  • Uyan, M., “GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/Turkey”. Renewable and Sustainable Energy Reviews, 28, 11-17, 2013.
  • Wang, B., Kocaoglu, D. F., Daim, T. U., & Yang, J., “A decision model for energy resource selection in China”. Energy Policy, 38(11), 7130-7141, 2010.
  • Yang, C. C., & Chen, B. S., “Supplier selection using combined analytical hierarchy process and grey relational analysis”. Journal of Manufacturing Technology Management, 17(7), 926-941, 2006.
  • Zhang, S. F., & Liu, S. Y., “A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection”. Expert Systems with Applications, 38(9), 11401-11405, 2011.
There are 44 citations in total.

Details

Journal Section Articles
Authors

Fatih Tüysüz 0000-0003-0203-4047

Publication Date December 11, 2017
Submission Date November 1, 2017
Published in Issue Year 2017

Cite

APA Tüysüz, F. (2017). A Hybrid Multi-Criteria Analysis Approach for the Assessment of Renewable Energy Resources Under Uncertainty. Alphanumeric Journal, 5(2), 317-328. https://doi.org/10.17093/alphanumeric.359662

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