Applications of multi-Criteria Decision-Making (MCDM) Methods in Renewable Energy Development: A Review

Document Type : Review Paper

Authors

¹ Faculty of New Sciences and Technologies, Tehran University, Tehran, Iran.

² Aerospace Engineering Department, Shahid Sattari Aeronautical University of Science and Technology, Tehran, Iran.

³ Department of Renewable Energies and Environmental, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran

https://doi.org/10.22044/rera.2020.8541.1006

Abstract

Renewable energies are noticeably developing due to their various advantages such as low greenhouse gases emission, availability and their reducing cost trend. In order to achieve the favorable objectives in energy projects, it is crucial to consider all the related parameters affecting the decision making. Multi Criteria Decision Making (MCDM) methods are reliable and efficient tool for policy making and achieving the most appropriate solution. These approaches consider the influential factors and their relative importance in prioritizing the alternatives. Since the outcome of the MCDM approaches depend on the employed algorithm and the used criteria, this article focuses on the studies related to the applications of these methods in renewable energy technology selection. The aim of the present paper is extracting the criteria which are necessary to be used in decision making for renewable energy systems. In addition, the approaches employed for improving the performance of MCDM methods as decision making aids are represented. According to this review study, technical, economic and environmental criteria are utilized in the majority of decision making researches. Moreover, some of the studies have considered other criteria such as social and risk to achieve more reliable decision. Some ideas are represented in the reviewed researches such as integrating different methods and using fuzzy sets, instead of crisp sets, to improve the performance of the MCDM methods and reduce the uncertainties.

Keywords

Main Subjects

Photovoltaic Systems

References

[1] Haghighi Bardineh Y, Mohamadian F, Ahmadi MH, Akbarianrad N. Medical and dental applications of renewable energy systems. Int J Low-Carbon Technol 2018;13:320–6.

[2] Ahmadi MH, Ghazvini M, Sadeghzadeh M, Alhuyi Nazari M, Kumar R, Naeimi A, et al. Solar power technology for electricity generation: A critical review. Energy Sci Eng 2018.

[3] Ramezanizadeh M, Alhuyi Nazari M, Hossein Ahmadi M, Chen L. A review on the approaches applied for cooling fuel cells. Int J Heat Mass Transf 2019;139:517–25.

[4] Dehghani Madvar M, Alhuyi Nazari M, Tabe Arjmand J, Aslani A, Ghasempour R, Ahmadi MH. Analysis of stakeholder roles and the challenges of solar energy utilization in Iran. Int J Low-Carbon Technol 2018;13:438–51.

[5] Alizadeh H, Ghasempour R, Shafii MB, Ahmadi MH, Yan W-M, Nazari MA. Numerical simulation of PV cooling by using single turn pulsating heat pipe. Int J Heat Mass Transf 2018;127:203–8.

[6] Ramezanizadeh M, Alhuyi Nazari M, Ahmadi MH, Açıkkalp E. Application of nanofluids in thermosyphons: A review. J Mol Liq 2018;272:395–402.

[7] Zhang W, Maleki A, Rosen MA, Liu J. Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage. Energy 2018;163:191–207.

[8] Maleki A, Khajeh MG, Ameri M. Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty. Int J Electr Power Energy Syst 2016;83:514–24.

[9] Ahmadi MH, Ramezanizadeh M, Nazari MA, Lorenzini G, Kumar R, Jilte R. Applications of nanofluids in geothermal: A review. Math Model Eng Probl 2018;5:281–5.

[10] Guangqian D, Bekhrad K, Azarikhah P, Maleki A. A hybrid algorithm based optimization on modeling of grid independent biodiesel-based hybrid solar/wind systems. Renew Energy 2018;122:551–60.

[11] Ahmadi MH, Alhuyi Nazari M, Ghasempour R, Pourfayaz F, Rahimzadeh M, Ming T. A review on solar‐assisted gas turbines. Energy Sci Eng 2018;6:658–74.

[12] Lu J, Ruan D. Multi-Objective Group Decision Making Methods, Software and Applications With Fuzzy Set Technique. Imperial College Press; 2007.

[13] Ahmadi MH, Sayyaadi H, Dehghani S, Hosseinzade H. Designing a solar powered Stirling heat engine based on multiple criteria: Maximized thermal efficiency and power. Energy Convers Manag 2013;75:282–91.

[14] Ahmadi MH, Ahmadi M-A, Mohammadi AH, Mehrpooya M, Feidt M. Thermodynamic optimization of Stirling heat pump based on multiple criteria. Energy Convers Manag 2014;80:319–28.

[15] Ahmadi MH, Mohammadi AH, Dehghani S, Barranco-Jiménez MA. Multi-objective thermodynamic-based optimization of output power of Solar Dish-Stirling engine by implementing an evolutionary algorithm. Energy Convers Manag 2013;75:438–45.

[16] Nigim K, Munier N, Green J. Pre-feasibility MCDM tools to aid communities in prioritizing local viable renewable energy sources. Renew Energy 2004;29:1775–91.

[17] Lee AHI, Chen HH, Kang H-Y. Multi-criteria decision making on strategic selection of wind farms. Renew Energy 2009;34:120–6.

[18] Şengül Ü, Eren M, Eslamian Shiraz S, Gezder V, Şengül AB. Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renew Energy 2015;75:617–25.

[19] Singh AK, Parida SK. A novel hybrid approach to allocate renewable energy sources in distribution system. Sustain Energy Technol Assessments 2015;10:1–11.

[20] Kumar A, Sah B, Singh AR, Deng Y, He X, Kumar P, et al. A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renew Sustain Energy Rev 2017;69:596–609.

[21] Pohekar SD, Ramachandran M. Application of multi-criteria decision making to sustainable energy planning—A review. Renew Sustain Energy Rev 2004;8:365–81.

[22] Alhuyi Nazari M, Aslani A, Ghasempour R. Analysis of Solar Farm Site Selection Based on TOPSIS Approach. Int J Soc Ecol Sustain Dev 2018;9.

[23] Gupta N. Material selection for thin-film solar cells using multiple attribute decision making approach. Mater Des 2011;32:1667–71.

[24] Strantzali E, Aravossis K. Decision making in renewable energy investments: A review. Renew Sustain Energy Rev 2016;55:885–98.

[25] R Abu-Taha. Multi-criteria applications in renewable energy analysis: A literature review. Proc. PICMET’11 Technol. Manag. Energy Smart World, IEEE; 2011, p. 1–8.

[26] Doukas HC, Andreas BM, Psarras JE. Multi-criteria decision aid for the formulation of sustainable technological energy priorities using linguistic variables. Eur J Oper Res 2007;182:844–55.

[27] Yazdani-Chamzini A, Fouladgar MM, Zavadskas EK, Moini SHH. Selecting the optimal renewable energy using multi criteria decision making. J Bus Econ Manag 2013;14:957–78.

[28] Çelikbilek Y, Tüysüz F. An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. Energy 2016;115:1246–58.

[29] Kahraman C, Kaya İ. A fuzzy multicriteria methodology for selection among energy alternatives. Expert Syst Appl 2010;37:6270–81.

[30] Kaya T, Kahraman C. Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology. Expert Syst Appl 2011;38:6577–85.

[31] Balin A, Barcli H. A Fuzzy multi-criteria decision making methodology based upon the interval type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey. Technol Econ Dev Econ 2015;23:742–63.

[32] Mardani A, Jusoh A, Zavadskas E, Cavallaro F, Khalifah Z, Mardani A, et al. Sustainable and Renewable Energy: An Overview of the Application of Multiple Criteria Decision Making Techniques and Approaches. Sustainability 2015;7:13947–84.

[33] Zhang L, Zhou P, Newton S, Fang J, Zhou D, Zhang L. Evaluating clean energy alternatives for Jiangsu, China: An improved multi-criteria decision making method. Energy 2015;90:953–64.

[34] Kahraman C, Kaya İ, Cebi S. A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process. Energy 2009;34:1603–16.

[35] Socorro García-Cascales M, Teresa Lamata M, Miguel Sánchez-Lozano J. Evaluation of photovoltaic cells in a multi-criteria decision making process. Ann Oper Res 2012;199:373–91.

[36] 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 2014;66:222–38.

[37] Çolak M, Kaya İ. Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey. Renew Sustain Energy Rev 2017;80:840–53.

[38] Kaya T, Kahraman C. Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul. Energy 2010;35:2517–27.

[39] Ahmadi MH, Ahmadi MA, Sadaghiani MS, Ghazvini M, Shahriar S, Alhuyi Nazari M. Ground source heat pump carbon emissions and ground-source heat pump systems for heating and cooling of buildings: A review. Environ Prog Sustain Energy 2017.

[40] Ahmadi MH, Ramezanizadeh M, Nazari MA, Lorenzini G, Kumar R, Jilte R. Applications of nanofluids in geothermal: A review. Math Model Eng Probl 2018;5:281–5.

[41] Rezaei MH, Sadeghzadeh M, Alhuyi Nazari M, Ahmadi MH, Astaraei FR. Applying GMDH artificial neural network in modeling CO2 emissions in four nordic countries. Int J Low-Carbon Technol 2018;13:266–71.

[42] Catalina T, Virgone J, Blanco E. Multi-source energy systems analysis using a multi-criteria decision aid methodology. Renew Energy 2011;36:2245–52.

[43] Demirtas O. Evaluating the best renewable energy technology for sustainable energy planning. Int J Energy Econ Policy 2013;3:23–33.

[44] Al Garni H, Kassem A, Awasthi A, Komljenovic D, Al-Haddad K. A multicriteria decision making approach for evaluating renewable power generation sources in Saudi Arabia. Sustain Energy Technol Assessments 2016;16:137–50.

[45] Wüstenhagen R, Wolsink M, Bürer MJ. Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy 2007;35:2683–91..