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Renewable Energy Technology Selection Problem Using Integrated H-SWARA-MULTIMOORA Approach

Author

Listed:
  • Abteen Ijadi Maghsoodi

    (Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Arta Ijadi Maghsoodi

    (Department of Chemical and Petroleum Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Amir Mosavi

    (Institute of Automation, Kando Kalman Faculty of Electrical Engineering, Obuda University, 1034 Budapest, Hungary
    Institute of Advanced Studies Koszeg, iASK, 9730 Koszeg, Hungary
    Institute of Structural Mechanics, Bauhaus Universität-Weimar, D-99423 Weimar, Germany)

  • Timon Rabczuk

    (Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia
    Institute of Structural Mechanics, Bauhaus Universität-Weimar, D-99423 Weimar, Germany)

  • Edmundas Kazimieras Zavadskas

    (Institute of Sustainable Construction, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania)

Abstract

Due to the adaptation of recent pollution mitigation and justification policies there has been a growing trend for electricity generation from various renewable resources. The selection of the optimal renewable energy technology could be measured as a complex problem due to the complication of forthcoming circumstances in any country. Consequently, the proposed similar complex assessment problem can be tackled with the support of Multiple Attribute Decision Making (MADM) methods. The current research study investigates a technology selection problem by proposing a hybrid MADM approach based on the Step-Wise Weight Assessment Ratio Analysis (SWARA) approach with a hierarchical arrangement combined with the Multi-Objective Optimization on the basis of Ratio Analysis plus the full MULTIplicative form (MULTIMOORA). Ultimately, a conceptual case study regarding the selection of the optimal renewable energy technology based on a conceptual development project in Iran has been examined by the proposed combinative MADM methodology.

Suggested Citation

  • Abteen Ijadi Maghsoodi & Arta Ijadi Maghsoodi & Amir Mosavi & Timon Rabczuk & Edmundas Kazimieras Zavadskas, 2018. "Renewable Energy Technology Selection Problem Using Integrated H-SWARA-MULTIMOORA Approach," Sustainability, MDPI, vol. 10(12), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:12:p:4481-:d:186199
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    References listed on IDEAS

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    11. Mujab Waqar & Kifayat Ullah & Dragan Pamucar & Goran Jovanov & Ðordje Vranješ, 2022. "An Approach for the Analysis of Energy Resource Selection Based on Attributes by Using Dombi T-Norm Based Aggregation Operators," Energies, MDPI, vol. 15(11), pages 1-23, May.
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    15. László Berényi & Zoltán Birkner & Nikolett Deutsch, 2020. "A Multidimensional Evaluation of Renewable and Nuclear Energy among Higher Education Students," Sustainability, MDPI, vol. 12(4), pages 1-22, February.
    16. Luiza Ossowska & Dorota Janiszewska & Natalia Bartkowiak-Bakun & Grzegorz Kwiatkowski, 2020. "Energy Consumption Versus Greenhouse Gas Emissions in EU," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 185-198.
    17. Yücenur, G. Nilay & Ipekçi, Ahmet, 2021. "SWARA/WASPAS methods for a marine current energy plant location selection problem," Renewable Energy, Elsevier, vol. 163(C), pages 1287-1298.
    18. Amir Mosavi & Mohsen Salimi & Sina Faizollahzadeh Ardabili & Timon Rabczuk & Shahaboddin Shamshirband & Annamaria R. Varkonyi-Koczy, 2019. "State of the Art of Machine Learning Models in Energy Systems, a Systematic Review," Energies, MDPI, vol. 12(7), pages 1-42, April.
    19. Heidary Dahooie, Jalil & Mohammadi, Navid & Daim, Tugrul & Vanaki, Amir Salar & Zavadskas, Edmundas Kazimieras, 2021. "Matching of technological forecasting technique to a technology using fuzzy multi-attribute decision-making methods: Case study from the aerospace industry," Technology in Society, Elsevier, vol. 67(C).

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