American Journal of Operations Management and Information Systems

Submit a Manuscript

Publishing with us to make your research visible to the widest possible audience.

Propose a Special Issue

Building a community of authors and readers to discuss the latest research and develop new ideas.

Using Multi-Criteria Decision-Making Techniques to Select Criteria in Renewable Energy

With global population increases, there is a noticeable change in pollution levels across the globe. This heightened environmental concern has played a significant role in sparking a growing demand for devices powered by renewable energy. The demand is not only a reflection of rising environmental awareness but is also driven by other factors, including the prospect of lower operating costs that renewable energy options can offer over their non-renewable counterparts. Renewable energy technology is a complex and rapidly evolving field. To effectively manage this growth, it has become crucial to carefully consider all the major parameters and constraints that impact the decision making process. This involves an understanding of technical parameters such as energy efficiency and durability, financial factors and environmental concerns such as the carbon footprint of the energy source. The task of integrating these diverse and often competing factors into a coherent decision making framework can be accomplished using Multi-Criteria Decision-Making (MCDM) techniques. These techniques have proven to be reliable and effective tools for tackling complex decision-making scenarios that involve multiple objectives. MCDM operates by identifying and prioritising the most viable alternatives within the decision space. This is done by considering the influential factors, or parameters and determining their relative importance to the overall decision making process. It should be noted that the application of MCDM is not merely theoretical. The analysis conducted using MCDM approaches incorporates the use of a sophisticated algorithm to deliver tangible and actionable output. The primary objective of this paper is to apply an MCDM approach specifically to the renewable energy technology sector. Further, it aims to identify and highlight the key criteria that are the most essential to the successful implementation and advancement of renewable energy systems.

Multi-criteria Decision-making Techniques, Renewable Energy, Optimised Criteria, Decision Space, Selection Criteria

Mahak Bhatia, Aled Williams. (2023). Using Multi-Criteria Decision-Making Techniques to Select Criteria in Renewable Energy. American Journal of Operations Management and Information Systems, 8(2), 21-29.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Fatih Karanfil and Yuanjing Li. Electricity consumption and economic growth: Exploring panel-specific differences. Energy policy, 82: 264-277, 2015.
2. Rajendra K Pachauri, Myles R Allen, Vicente R Barros, John Broome, Wolfgang Cramer, Renate Christ, John A Church, Leon Clarke, Qin Dahe, Purnamita Dasgupta, et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report ofthe IntergovernmentalPanel onClimate Change. IPCC, 2014.
3. Payam Nejat, Fatemeh Jomehzadeh, Mohammad Mahdi Taheri, Mohammad Gohari, and Muhd Zaimi Abd Majid. A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries). Renewable and sustainable energy reviews, 43: 843-862, 2015.
4. Mariam Gómez Sánchez, Yunesky Masip Macia, Alejandro Fernández Gil, Carlos Castro, Suleivys M Nu ñez González, and Jacqueline Pedrera Yanes. A mathematical model for the optimization of renewable energy systems. Mathematics, 9 (1): 39, 2020.
5. Bhavana Saini, MA Ansari, and Vinaya Rana. Design of micro-grid using hybrid energy source for remote location application. In 2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC), pages 556-560. IEEE, 2019.
6. Rob Smith. Three countries are leading the renewable energy revolution. In World Economic Forum, volume 26, 2018.
7. Reza Alizadeh, Leili Soltanisehat, Peter D Lund, and Hamed Zamanisabzi. Improving renewable energy policy planning and decision-making through a hybrid mcdm method. Energy Policy, 137: 111174, 2020.
8. Mohammad Hossein Ahmadi, Mahyar Ghazvini, Milad Sadeghzadeh, Mohammad Alhuyi Nazari, Ravinder Kumar, Abbas Naeimi, and Tingzhen Ming. Solar power technology for electricity generation: A critical review. Energy Science & Engineering, 6 (5): 340-361, 2018.
9. Du Guangqian, Kaveh Bekhrad, Pouria Azarikhah, and Akbar Maleki. A hybrid algorithm based optimization on modeling of grid independent biodiesel-based hybrid solar/wind systems. Renewable Energy, 122: 551-560, 2018.
10. Laura Cozzi. The world’s top 1% of emitters produce over 10,000 times more CO2 than the bottom 1%. International Energy Agency (IEA): bottom-1, February 2023. 11.
11. Marko Bohanec, Nejc Trdin, and Branko Konti’c. A qualitative multi-criteria modelling approach to the assessment of electric energy production technologies in slovenia. Central European Journal of Operations Research, 25: 611-625, 2017.
12. Theocharis Tsoutsos, Maria Drandaki, Niki Frantzeskaki, Eleftherios Iosifidis, and Ioannis Kiosses. Sustainable energy planning by using multi-criteria analysis application in the island of crete. Energy policy, 37 (5): 1587-1600, 2009.
13. Xiaoyan Qian, Yang Bai, Weilun Huang, Jie Dai, Xuan Li, and Yuanzhu Wang. Fuzzy technique application in selecting photovoltaic energy and solar thermal energy production in belt and road countries. Journal of Energy Storage, 41: 102865, 2021.
14. Jiang-Jiang Wang, You-Yin Jing, Chun-Fa Zhang, and Jun-Hong Zhao. Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and sustainable energy reviews, 13 (9): 2263- 2278, 2009.
15. Douglas Broom. These 4 charts show the state of renewable energy in 2022. World Economic Forum: of-renewable-energy-2022/, June 2022.
16. Elisabeth Ilskog. Indicators for assessment of rural electrification - an approach for the comparison of apples and pears. Energy policy, 36 (7): 2665-2673, 2008.
17. Fred S Azar. Multiattribute decision-making: use of three scoring methods to compare the performance of imaging techniques for breast cancer detection. University of Pennsylvania Department of Computer and Information Science Technical Report, 2000.
18. D Diakoulaki, G Mavrotas, and L Papayannakis. Determing objective weights in multiple criteria problems: the critic method, computers & operational research, 1995.
19. Mehdi Keshavarz-Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis, and Jurgita Antucheviciene. Determination of objective weights using a new method based on the removal effects of criteria (merec). Symmetry, 13 (4): 525, 2021.
20. Jie Lu and Da Ruan. Multi-objective group decision making: methods, software and applications with fuzzy set techniques, volume 6. Imperial College Press, 2007.
21. Sangram Bana and RP Saini. A mathematical modeling framework to evaluate the performance of single diode and double diode based spv systems. energy reports, 2016.
22. Matthias Ehrgott. Multicriteria optimization, volume 491. Springer Science & Business Media, 2005.