Document Type : Original Article

Authors

1 Department of Mechanics, Germi Branch, Islamic Azad University, Germi, Iran.

2 Department of Agricultural Mechanization, Germi Branch, Islamic Azad University, Germi, Iran.

Abstract

Today, policymakers are aware of the substantial advantages of renewable energies. From the point of view of national and regional decision-makers, the first priority of preparing a com-prehensive energy plan and the second priority of determining the share of renewable energy in the total energy production basket of the country is an essential step in the energy policy pro-cess. In choosing from various renewable energy options, environmental dimensions are com-bined with economic, technical, and social criteria, which shows the need to combine these crite-ria, the multi-criteria of the governing decision-making space, and policy-making. Multi-criteria decision-making techniques can play an important role in choosing the best solution and option. The statistical population of this study is eight cities in the case study. The renewable energy sources studied include wind, solar, water, geothermal, and biomass. First, the potential of re-newable energy for the study areas was identified. Then the two main criteria of sustainable de-velopment: economic criteria with 5 sub-criteria and environmental criteria with 3 sub-criteria were analyzed. Finally, using the Economic Analytic Network Process (ANP) sub criterion, the environmental sub-criterion of each of the weighted renewable energies was allocated. One of the essential results of this research is the income of 72868.8 $ from solar power in Ardabil. The cost of energy is $ 2.72 kWh. The lowest cost per unit of energy produced is related to Khalkhal geothermal energy at $ 0.144.

Keywords

Main Subjects

[1] Büyüközkan, G. and Karabulut, Y. (2017). Energy project performance evaluation with sustainability perspective. Energy, 119, 549-560.
 
[2] Bhardwaj, A., Joshi, M., Khosla, R., and Dubash, N. K. (2019). More priorities, more problems? Decision-making with multiple energy, development and climate objectives. Energy Research & Social Science, 49, 143-157.
 
[3] Ilbahar, E., Cebi, S., and Kahraman, C. (2019). A state-of-the-art review on multi-attribute renewable energy decision-making. Energy Strategy Reviews, 25, 18-33.
 
[4] Estévez, R. A., Espinoza, V., Ponce Oliva, R. D., Vásquez-Lavín, F., and Gelcich, S. (2021). Multi-Criteria Decision Analysis for Renewable Energies: Research Trends, Gaps and the Challenge of Improving Participation. Sustainability, 13(6), 3515.
 
[5] Wang, C. N., Thanh, N. V., and Su, C. C. (2019). The Study of a Multicriteria Decision Making Model for Wave Power Plant Location Selection in Vietnam. Processes, 7(10), 650.
 
[6] Siksnelyte, I., Zavadskas, E. K., Streimikiene, D., and Sharma, D. (2018). An overview of multi-criteria decision-making methods in dealing with sustainable energy development issues. Energies, 11(10), 2754.
 
[7] Mallikarjun, S. and Lewis, H. F. (2014). Energy technology allocation for distributed energy resources: A strategic technology-policy framework. Energy, 72, 783-799.
 
[8] Bottero, M., Dell’Anna, F., and Morgese, V. (2021). Evaluating the Transition towards Post-Carbon Cities: A Literature Review. Sustainability, 13(2), 567.
 
[9] Siksnelyte-Butkiene, I., Zavadskas, E. K., and Streimikiene, D. (2020). Multi-criteria decision-making (MCDM) for the assessment of renewable energy technologies in a household: A review. Energies, 13(5), 1164.
 
[10] Ishak, A. and Akmaliah, V. (2020, April). Technology assessment of liquid waste in rubber factory using analytical hierarchy process and promethee methods. In AIP Conference Proceedings (Vol. 2217, No. 1, p. 030059). AIP Publishing LLC.
 
[11] Ibáñez-Forés, V., Bovea, M. D., and Pérez-Belis, V. (2014). A holistic review of applied methodologies for assessing and selecting the optimal technological alternative from a sustainability perspective. Journal of Cleaner Production, 70, 259-281.
 
[12] Özcan, E. C., Ünlüsoy, S., & Eren, T. (2017). A combined goal programming–AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants. Renewable and Sustainable Energy Reviews, 78, 1410-1423.
 
[13] Ezbakhe, F. and Pérez-Foguet, A. (2021). Decision analysis for sustainable development: The case of renewable energy planning under uncertainty. European Journal of Operational Research, 291(2), 601-613.
 
[14] Yazdani, M., Chatterjee, P., Zavadskas, E. K., and Streimikiene, D. (2018). A novel integrated decision-making approach for the evaluation and selection of renewable energy technologies. Clean Technologies and Environmental Policy, 20(2), 403-420.
 
[15] Yazdani, M., Torkayesh, A. E., Santibanez-Gonzalez, E. D., and Otaghsara, S. K. (2020). Evaluation of renewable energy resources using integrated Shannon Entropy—EDAS model. Sustainable Operations and Computers, 1, 35-42.
 
[16] Solangi, Y. A., Tan, Q., Mirjat, N. H., Valasai, G. D., Khan, M. W. A., and Ikram, M. (2019). An integrated Delphi-AHP and fuzzy TOPSIS approach toward ranking and selection of renewable energy resources in Pakistan. Processes, 7(2), 118.
 
[17] Li, T., Li, A., and Guo, X. (2020). The sustainable development-oriented development and utilization of renewable energy industry——A comprehensive analysis of MCDM methods. Energy, 212, 118694.
 
[18] Troldborg, M., Heslop, S., and Hough, R. L. (2014). Assessing the sustainability of renewable energy technologies using multi-criteria analysis: Suitability of approach for national-scale assessments and associated uncertainties. Renewable and sustainable energy reviews, 39, 1173-1184.
 
[19] Malla, S. and Timilsina, G. R. (2016). Long-term energy demand forecasting in Romania: an end-user demand. World Bank Policy Research Working Paper, (7697).
 
[20] Khanna, R. A., Li, Y., Mhaisalkar, S., Kumar, M., and Liang, L. J. (2019). Comprehensive energy poverty index: Measuring energy poverty and identifying micro-level solutions in South and Southeast Asia. Energy Policy, 132, 379-391.
 
[21] Shokatpour, M. H., Nazari, M. A., and Assad, M. E. H. (2022, February). Renewable Energy Technology Selection for Iran by Using Multi Criteria Decision Making. In 2022 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-4). IEEE.‏
 
[22] Abdullah, L. and Najib, L. (2016). Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia. International Journal of Sustainable Energy, 35(4), 360-377.
 
[23] Shad, R., Khorrami, M., and Ghaemi, M. (2017). Developing an Iranian green building assessment tool using decision making methods and geographical information system: Case study in Mashhad city. Renewable and Sustainable Energy Reviews, 67, 324-340.
 
[24] Nazari, M. A., Assad, M. E. H., Haghighat, S., and Maleki, A. (2020, February). Applying TOPSIS method for wind farm site selection in Iran. In 2020 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-4). IEEE.‏
 
[25] Blanco, G., Amarilla, R., Martinez, A., Llamosas, C., and Oxilia, V. (2017). Energy transitions and emerging economies: A multi-criteria analysis of policy options for hydropower surplus utilization in Paraguay. Energy Policy, 108, 312-321.
 
[26] Abotah, R. and Daim, T. U. (2017). Towards building a multi perspective policy development framework for transition into renewable energy. Sustainable Energy Technologies and Assessments, 21, 67-88.
 
[27] Baseer, M. A., Rehman, S., Meyer, J. P., and Alam, M. M. (2017). GIS-based site suitability analysis for wind farm development in Saudi Arabia. Energy, 141, 1166-1176.
 
[28] Ozmen, M., Aydogan, E. K., Ates, N., and Uzal, N. (2016). Developing a decision-support system for waste management in aluminum production. Environmental Modeling & Assessment, 21(6), 803-817.
 
[29] Gao, R., Nam, H. O., Ko, W. I., and Jang, H. (2017). National options for a sustainable nuclear energy system: MCDM evaluation using an improved integrated weighting approach. Energies, 10(12).
 
[30] Ligus, M. (2017). Evaluation of economic, social and environmental effects of low-emission energy technologies development in Poland: A multi-criteria analysis with application of a fuzzy analytic hierarchy process (FAHP). Energies, 10(10), 1550.
 
[31] Yu, X., Chen, H., and Ji, Z. (2019). Combination of probabilistic linguistic term sets and PROMETHEE to evaluate meteorological disaster risk: Case study of southeastern China. Sustainability, 11(5), 1405.
 
[32] Seddiki, M., & Bennadji, A. (2019). Multi-criteria evaluation of renewable energy alternatives for electricity generation in a residential building. Renewable and sustainable energy reviews, 110, 101-117.
 
[33] Debbarma, B., Chakraborti, P., Bose, P. K., Deb, M., and Banerjee, R. (2017). Exploration of PROMETHEE II and VIKOR methodology in a MCDM approach for ascertaining the optimal performance-emission trade-off vantage in a hydrogen-biohol dual fuel endeavour. Fuel, 210, 922-935.
 
[34] Alayi, R., Kasaeian, A., Najafi, A., and Jamali, E. (2020). Optimization and evaluation of a wind, solar and fuel cell hybrid system in supplying electricity to a remote district in national grid. International Journal of Energy Sector Management, 14(2), 408-418.‏
 
[35] Mladineo, M., Veza, I., and Gjeldum, N. (2017). Solving partner selection problem in cyber-physical production networks using the HUMANT algorithm. International Journal of Production Research, 55(9), 2506-2521.