A Review of Multi-Criteria Decision-Making Applications to Solve Energy Management Problems From 2010-2025: Current State and Future Research

Authors

  • Sushil Kumar Sahoo Department of Mechanical Engineering, Indira Gandhi Institute of Technology, Sarang (BPUT), Odisha, India Author https://orcid.org/0000-0002-8551-7353
  • Dragan Pamucar 1) Department of Applied Mathematical Science, College of Science and Technology, Korea University, Sejong 30019, Republic of Korea; 2) Department of Industrial Engineering & Management, Yuan Ze University, Taoyuan City, Taiwan; 3) Széchenyi István University, Győr, Hungary Author https://orcid.org/0000-0001-8522-1942
  • Shankha Shubhra Goswami Department of Mechanical Engineering, Abacus Institute of Engineering and Management, Hooghly, West Bengal, India Author https://orcid.org/0000-0002-0033-3089

DOI:

https://doi.org/10.31181/sdmap21202525

Keywords:

MCDM, Energy Management, Renewable Energy Systems, Sustainable Energy Planning, Bibliometric Analysis

Abstract

Energy management is a critical challenge in the global effort to achieve sustainability, improve efficiency, and balance economic and environmental priorities. Multi-Criteria Decision-Making (MCDM) techniques have emerged as powerful tools to address complex and competing criteria in energy systems. This paper reviews the current state of MCDM applications in energy management, focusing on renewable energy systems, energy efficiency, grid management, and policy planning from 2010-2025 using bibliometric analysis. It identifies popular methods such as AHP, TOPSIS, and hybrid models, highlighting their strengths and limitations. The analysis reveals trends, gaps, and challenges, such as handling uncertainty, integrating real-time data, and adapting to dynamic energy environments. Future research directions emphasize leveraging advanced technologies like artificial intelligence, blockchain, and IoT to enhance MCDM models and expanding their application to emerging areas like microgrids and sustainable urban systems. This review provides a comprehensive understanding of the field and outlines a roadmap for advancing MCDM applications in solving energy management problems.

Downloads

Download data is not yet available.

References

Moazzen, F., & Hossain, M. J. (2025). A two-layer strategy for sustainable energy management of microgrid clusters with embedded energy storage system and demand-side flexibility provision. Applied Energy, 377, 124659. https://doi.org/10.1016/j.apenergy.2024.124659

Achuo, E., Kakeu, P., & Asongu, S. (2025). Financial development, human capital and energy transition: A global comparative analysis. International Journal of Energy Sector Management, 19(1), 59-80. https://doi.org/10.1108/IJESM-11-2023-0004

Groppi, D., Pastore, L. M., Nastasi, B., Prina, M. G., Garcia, D. A., & de Santoli, L. (2025). Energy modelling challenges for the full decarbonisation of hard-to-abate sectors. Renewable and Sustainable Energy Reviews, 209, 115103. https://doi.org/10.1016/j.rser.2024.115103

Sandra, M., Narayanamoorthy, S., Suvitha, K., Pamucar, D., Simic, V., & Kang, D. (2025). An insightful multicriteria model for the selection of drilling technique for heat extraction from geothermal reservoirs using a fuzzy-rough approach. Information Sciences, 686, 121353. https://doi.org/10.1016/j.ins.2024.121353

Amponsah, N. Y., Troldborg, M., Kington, B., Aalders, I., & Hough, R. L. (2014). Greenhouse gas emissions from renewable energy sources: A review of lifecycle considerations. Renewable and Sustainable Energy Reviews, 39, 461-475. https://doi.org/10.1016/j.rser.2014.07.087

Ahmmad, J., Mahmood, T., Pamucar, D., & Waqas, H. M. (2025). A novel Complex q-rung orthopair fuzzy Yager Aggregation Operators and Their Applications in Environmental Engineering. Heliyon. DOI: 10.1016/j.heliyon.2025.e41668

Pamucar, D., Deveci, M., Stević, Ž., Gokasar, I., Isik, M., & Coffman, D. M. (2022). Green strategies in mobility planning towards climate change adaption of urban areas using fuzzy 2D algorithm. Sustainable Cities and Society, 87, 104159. https://doi.org/10.1016/j.scs.2022.104159

Yang, Y., Wang, W., Qin, J., Wang, M., Ma, Q., & Zhong, Y. (2024). Review of vehicle to grid integration to support power grid security. Energy Reports, 12, 2786-2800.

Sahoo, S. K., & Goswami, S. S. (2023). A comprehensive review of multiple criteria decision-making (MCDM) Methods: advancements, applications, and future directions. Decision Making Advances, 1(1), 25-48. https://doi.org/10.31181/dma1120237

Kshanh, I., & Tanaka, M. (2024). Comparative analysis of MCDM for energy efficiency projects evaluation towards sustainable industrial energy management: case study of a petrochemical complex. Expert Systems with Applications, 255, 124692. https://doi.org/10.1016/j.eswa.2024.124692

Sahoo, S. K., & Choudhury, B. B. (2023). Evaluating Material Alternatives for low cost Robotic Wheelchair Chassis: A Combined CRITIC, EDAS, and COPRAS Framework. Jordan Journal of Mechanical & Industrial Engineering, 17(4). https://doi.org/10.59038/jjmie/170419

Sotoudeh-Anvari, A. (2022). The applications of MCDM methods in COVID-19 pandemic: A state of the art review. Applied Soft Computing, 126, 109238. https://doi.org/10.1016/j.asoc.2022.109238

Sahoo, S. K., & Choudhury, B. B. (2024). An Integrated MCDM Framework for Optimizing Rotary Actuator Selection in Smart Robotic Power Wheelchair Prototypes. Jordan Journal of Mechanical & Industrial Engineering, 18(3). https://doi.org/10.59038/jjmie/180311

Parvaneh, F., & Hammad, A. (2024). Application of Multi-Criteria Decision-Making (MCDM) to Select the Most Sustainable Power-Generating Technology. Sustainability, 16(8), 3287. https://doi.org/10.3390/su16083287

Saraswat, S. K., Digalwar, A. K., & Vijay, V. (2024). Analysis of Multi-renewable Energy Potential Sites in India Using Spatial Characteristics: A GIS and Hybrid MCDM Approach. Process Integration and Optimization for Sustainability, 8(5), 1493-1526. https://doi.org/10.1007/s41660-024-00441-3

Uzair, M., & Kazmi, S. A. A. (2023). A multi-criteria decision model to support sustainable building energy management system with intelligent automation. Energy and Buildings, 301, 113687. https://doi.org/10.1016/j.enbuild.2023.113687

Schaefer, J. L., Siluk, J. C. M., & de Carvalho, P. S. (2021). An MCDM-based approach to evaluate the performance objectives for strategic management and development of Energy Cloud. Journal of Cleaner Production, 320, 128853. https://doi.org/10.1016/j.jclepro.2021.128853

Habibzadeh, S., Astaraei, F. R., & Jahangir, M. H. (2025). Sustainability assessment of a petrochemical plant electricity supply based on 4E optimization of various hybrid renewable energy systems scenarios. Energy Conversion and Management, 325, 119357. https://doi.org/10.1016/j.enconman.2024.119357

Wen, H., Liu, X., Yang, M., Lei, B., Cheng, X., & Chen, Z. (2023). An energy demand-side management and net metering decision framework. Energy, 271, 127075. https://doi.org/10.1016/j.energy.2023.127075

Hassan, M., Khan Afridi, M., & Irfan Khan, M. (2019). Energy policies and environmental security: A multi-criteria analysis of energy policies of Pakistan. International Journal of Green Energy, 16(7), 510-519. https://doi.org/10.1080/15435075.2019.1593177

Alizadeh, R., Soltanisehat, L., Lund, P. D., & Zamanisabzi, H. (2020). Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy, 137, 111174. https://doi.org/10.1016/j.enpol.2019.111174

Kumar, R., & Sahoo, S. K. (2025). A Bibliometric Analysis of Agro-Based Industries: Trends and Challenges in Supply Chain Management. Decision Making Advances, 3(1), 200-215. https://doi.org/10.31181/dma31202568

Sahoo, S. K., Choudhury, B. B., & Dhal, P. R. (2024). A bibliometric analysis of material selection using MCDM methods: trends and insights. Spectrum of Mechanical Engineering and Operational Research, 1(1), 189-205. https://doi.org/10.31181/smeor11202417

Mourao, P. R., & Martinho, V. D. (2020). Forest entrepreneurship: A bibliometric analysis and a discussion about the co-authorship networks of an emerging scientific field. Journal of Cleaner Production, 256, 120413. https://doi.org/10.1016/j.jclepro.2020.120413

Demir, G., Chatterjee, P., Zakeri, S., & Pamucar, D. (2024). Mapping the evolution of multi-attributive border approximation area comparison method: a bibliometric analysis. Decision Making: Applications in Management and Engineering, 7(1), 290-314. https://doi.org/10.31181/dmame7120241037

Demir, G., Chatterjee, P., & Pamucar, D. (2024). Sensitivity analysis in multi-criteria decision making: A state-of-the-art research perspective using bibliometric analysis. Expert Systems with Applications, 237, 121660. https://doi.org/10.1016/j.eswa.2023.121660

Bai, X., Aw, E. C. X., Tan, G. W. H., & Ooi, K. B. (2024). Livestreaming as the next frontier of e-commerce: A bibliometric analysis and future research agenda. Electronic Commerce Research and Applications, 101390. https://doi.org/10.1016/j.elerap.2024.101390

Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with applications, 39(17), 13051-13069. https://doi.org/10.1016/j.eswa.2012.05.056

Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and sustainable energy reviews, 69, 596-609. https://doi.org/10.1016/j.rser.2016.11.191

Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Science of the total environment, 409(19), 3578-3594. https://doi.org/10.1016/j.scitotenv.2011.06.022

Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications–Two decades review from 1994 to 2014. Expert systems with Applications, 42(8), 4126-4148. https://doi.org/10.1016/j.eswa.2015.01.003

Mardani, A., Jusoh, A., Zavadskas, E. K., Cavallaro, F., & Khalifah, Z. (2015). Sustainable and renewable energy: An overview of the application of multiple criteria decision making techniques and approaches. Sustainability, 7(10), 13947-13984. https://doi.org/10.3390/su71013947

Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and economic development of economy, 20(1), 165-179. https://doi.org/10.3846/20294913.2014.892037

San Cristóbal, J. R. (2011). Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method. Renewable energy, 36(2), 498-502. https://doi.org/10.1016/j.renene.2010.07.031

Sánchez-Lozano, J. M., Teruel-Solano, J., Soto-Elvira, P. L., & García-Cascales, M. S. (2013). Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain. Renewable and sustainable energy reviews, 24, 544-556. https://doi.org/10.1016/j.rser.2013.03.019

Lee, H. C., & Chang, C. T. (2018). Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and sustainable energy reviews, 92, 883-896.https://doi.org/10.1016/j.rser.2018.05.007

Suganthi, L., Iniyan, S., & Samuel, A. A. (2015). Applications of fuzzy logic in renewable energy systems–a review. Renewable and sustainable energy reviews, 48, 585-607. https://doi.org/10.1016/j.rser.2015.04.037

Ahmad, T., Madonski, R., Zhang, D., Huang, C., & Mujeeb, A. (2022). Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm. Renewable and Sustainable Energy Reviews, 160, 112128. https://doi.org/10.1016/j.rser.2022.112128

Liu, P., Zhang, T., Tian, F., Teng, Y., & Yang, M. (2024). Optimized grid partitioning and scheduling in multi-energy systems using a hybrid decision-making approach. Energies, 17(13), 3253. https://doi.org/10.3390/en17133253

Otay, İ., Onar, S. Ç., Öztayşi, B., & Kahraman, C. (2024). Evaluation of sustainable energy systems in smart cities using a Multi-Expert Pythagorean fuzzy BWM & TOPSIS methodology. Expert Systems with Applications, 250, 123874. https://doi.org/10.1016/j.eswa.2024.123874

Rezk, H., Olabi, A. G., Mahmoud, M., Wilberforce, T., & Sayed, E. T. (2024). Metaheuristics and multi-criteria decision-making for renewable energy systems: Review, progress, bibliometric analysis, and contribution to the sustainable development pillars. Ain Shams Engineering Journal, 102883. https://doi.org/10.1016/j.asej.2024.102883

Published

2025-01-23

How to Cite

Sahoo, S. K., Pamucar, D., & Goswami, S. S. (2025). A Review of Multi-Criteria Decision-Making Applications to Solve Energy Management Problems From 2010-2025: Current State and Future Research. Spectrum of Decision Making and Applications, 2(1), 219-241. https://doi.org/10.31181/sdmap21202525