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Examining wind energy deployment pathways in complex macro-economic and political settings using a fuzzy cognitive map-based method

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  • Ghaboulian Zare, Sara
  • Alipour, Mohammad
  • Hafezi, Mehdi
  • Stewart, Rodney A.
  • Rahman, Anisur

Abstract

Long-term sustainable wind energy deployment faces an array of challenges due to various complex interconnected impediment factors. These inherent endogenous and exogenous uncertainties preclude obtaining an accurate future trend, which in turn complicates the design of the good policy. This study employs Fuzzy Cognitive Maps (FCMs) to semi-quantitatively explore the scenarios of wind energy deployment in Iran. The FCM-based framework was built using participatory workshops and a subsequent questionnaire survey to identify 26 influential factors shaping the dynamics of the system. The developed scenarios originated from the latest narratives of real-world geopolitical variations. The findings demonstrated that the sector is governed by six major groupings of factors predominated by economic and political concepts with strong interconnections between them. Five key concepts, including two economic, one legal, and two political, were ascertained that contribute to the stability of the system. Of the four scenarios, only one optimistic trajectory expects an acceleration in the deployment. Another scenario projects that there will not be any considerable change between the future scheme and the current state of development. However, the other scenarios envisage a substantially slower growth than the current trend.

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  • Ghaboulian Zare, Sara & Alipour, Mohammad & Hafezi, Mehdi & Stewart, Rodney A. & Rahman, Anisur, 2022. "Examining wind energy deployment pathways in complex macro-economic and political settings using a fuzzy cognitive map-based method," Energy, Elsevier, vol. 238(PA).
  • Handle: RePEc:eee:energy:v:238:y:2022:i:pa:s0360544221019216
    DOI: 10.1016/j.energy.2021.121673
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    References listed on IDEAS

    as
    1. Feng, Y.Y. & Chen, S.Q. & Zhang, L.X., 2013. "System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China," Ecological Modelling, Elsevier, vol. 252(C), pages 44-52.
    2. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    3. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    4. Abbaszadeh, Payam & Maleki, Abbas & Alipour, Mohammad & Maman, Yaser Kanani, 2013. "Iran's oil development scenarios by 2025," Energy Policy, Elsevier, vol. 56(C), pages 612-622.
    5. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    6. Baur, Lucia & Uriona M., Mauricio, 2018. "Diffusion of photovoltaic technology in Germany: A sustainable success or an illusion driven by guaranteed feed-in tariffs?," Energy, Elsevier, vol. 150(C), pages 289-298.
    7. Huang, Shih-Chieh & Lo, Shang-Lien & Lin, Yen-Ching, 2013. "Application of a fuzzy cognitive map based on a structural equation model for the identification of limitations to the development of wind power," Energy Policy, Elsevier, vol. 63(C), pages 851-861.
    8. Amirkhani, Abdollah & Papageorgiou, Elpiniki I. & Mosavi, Mohammad R. & Mohammadi, Karim, 2018. "A novel medical decision support system based on fuzzy cognitive maps enhanced by intuitive and learning capabilities for modeling uncertainty," Applied Mathematics and Computation, Elsevier, vol. 337(C), pages 562-582.
    9. Konstantinos Papageorgiou & Gustavo Carvalho & Elpiniki I. Papageorgiou & Dionysis Bochtis & George Stamoulis, 2020. "Decision-Making Process for Photovoltaic Solar Energy Sector Development using Fuzzy Cognitive Map Technique," Energies, MDPI, vol. 13(6), pages 1-23, March.
    10. Zanjirchi, Seyed Mahmoud & Shojaei, Sara & Naser Sadrabadi, Alireza & Jalilian, Negar, 2020. "Promotion of solar energies usage in Iran: A scenario-based road map," Renewable Energy, Elsevier, vol. 150(C), pages 278-292.
    11. Alipour, Mohammad & Hafezi, Reza & Ervural, Bilal & Kaviani, Mohamad Amin & Kabak, Özgür, 2018. "Long-term policy evaluation: Application of a new robust decision framework for Iran's energy exports security," Energy, Elsevier, vol. 157(C), pages 914-931.
    12. Solana-Gutiérrez, Joaquín & Rincón, Gonzalo & Alonso, Carlos & García-de-Jalón, Diego, 2017. "Using fuzzy cognitive maps for predicting river management responses: A case study of the Esla River basin, Spain," Ecological Modelling, Elsevier, vol. 360(C), pages 260-269.
    13. Naeini, Mina Alavi & Zandieh, Mostafa & Najafi, Seyyed Esmaeil & Sajadi, Seyed Mojtaba, 2020. "Analyzing the development of the third-generation biodiesel production from microalgae by a novel hybrid decision-making method: The case of Iran," Energy, Elsevier, vol. 195(C).
    14. Linmao Ma & Jing Yu & Long Zhang, 2019. "An Analysis on Barriers to Biomass and Bioenergy Development in Rural China Using Intuitionistic Fuzzy Cognitive Map," Energies, MDPI, vol. 12(9), pages 1-23, April.
    15. Alipour, M. & Alighaleh, S. & Hafezi, R. & Omranievardi, M., 2017. "A new hybrid decision framework for prioritizing funding allocation to Iran's energy sector," Energy, Elsevier, vol. 121(C), pages 388-402.
    16. Aslani, Alireza & Helo, Petri & Naaranoja, Marja, 2014. "Role of renewable energy policies in energy dependency in Finland: System dynamics approach," Applied Energy, Elsevier, vol. 113(C), pages 758-765.
    17. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2021. "Residential solar photovoltaic adoption behaviour: End-to-end review of theories, methods and approaches," Renewable Energy, Elsevier, vol. 170(C), pages 471-486.
    18. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    19. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2020. "Predictors, taxonomy of predictors, and correlations of predictors with the decision behaviour of residential solar photovoltaics adoption: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    20. Ziv, Guy & Watson, Elizabeth & Young, Dylan & Howard, David C. & Larcom, Shaun T. & Tanentzap, Andrew J., 2018. "The potential impact of Brexit on the energy, water and food nexus in the UK: A fuzzy cognitive mapping approach," Applied Energy, Elsevier, vol. 210(C), pages 487-498.
    21. Song, Jinbo & Sun, Yan & Jin, Lulu, 2017. "PESTEL analysis of the development of the waste-to-energy incineration industry in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 276-289.
    22. Bhattacharyya, Subhes C. & Timilsina, Govinda R., 2010. "Modelling energy demand of developing countries: Are the specific features adequately captured?," Energy Policy, Elsevier, vol. 38(4), pages 1979-1990, April.
    23. Alipour, M. & Hafezi, R. & Amer, M. & Akhavan, A.N., 2017. "A new hybrid fuzzy cognitive map-based scenario planning approach for Iran's oil production pathways in the post–sanction period," Energy, Elsevier, vol. 135(C), pages 851-864.
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