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Assessment of Urban Wind Potential and the Stakeholders Involved in Energy Decision-Making

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  • Alexander Vallejo Díaz

    (Instituto Especializado de Estudios Superiores Loyola, San Cristóbal 91000, Dominican Republic
    Instituto Tecnológico de Santo Domingo, Santo Domingo 10602, Dominican Republic)

  • Idalberto Herrera Moya

    (Instituto Especializado de Estudios Superiores Loyola, San Cristóbal 91000, Dominican Republic
    Instituto Tecnológico de Santo Domingo, Santo Domingo 10602, Dominican Republic
    Facultad de Ingeniería Mecánica e Industrial, Universidad Central “Marta Abreu” de Las Villas (UCLV), Santa Clara 54830, Cuba)

  • Edwin Garabitos Lara

    (Instituto Especializado de Estudios Superiores Loyola, San Cristóbal 91000, Dominican Republic)

  • Cándida K. Casilla Victorino

    (Instituto Especializado de Estudios Superiores Loyola, San Cristóbal 91000, Dominican Republic)

Abstract

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advancement in technologies for the use of urban wind energy has offered an alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open access NWP tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consulted, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found that 24 provinces have poor potentials, below <4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 and 6.63 m/s. The population density was established, and it was observed that the provinces with greater potential are less densely populated. Through 59 interviews, 28 institutions were identified and evaluated due to their relevance in decision making for the implementation of energy projects. According to the RACI matrix, the Ministry of Energy and Mines has been categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

Suggested Citation

  • Alexander Vallejo Díaz & Idalberto Herrera Moya & Edwin Garabitos Lara & Cándida K. Casilla Victorino, 2024. "Assessment of Urban Wind Potential and the Stakeholders Involved in Energy Decision-Making," Sustainability, MDPI, vol. 16(4), pages 1-20, February.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1362-:d:1334164
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    References listed on IDEAS

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    1. Karkowska, Renata & Urjasz, Szczepan, 2023. "How does the Russian-Ukrainian war change connectedness and hedging opportunities? Comparison between dirty and clean energy markets versus global stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    2. Michael G. Pollitt, 2015. "In Search of 'Good' Energy Policy: The Social Limits to Technological Solutions to Energy and Climate Problems," Working Papers EPRG 1520, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    3. Satya Widya Yudha & Benny Tjahjono, 2019. "Stakeholder Mapping and Analysis of the Renewable Energy Industry in Indonesia," Energies, MDPI, vol. 12(4), pages 1-19, February.
    4. Schlindwein, L.F. & Montalvo, C., 2023. "Energy citizenship: Accounting for the heterogeneity of human behaviours within energy transition," Energy Policy, Elsevier, vol. 180(C).
    5. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    6. Simões, Teresa & Estanqueiro, Ana, 2016. "A new methodology for urban wind resource assessment," Renewable Energy, Elsevier, vol. 89(C), pages 598-605.
    7. Alice Altissimo, 2016. "Combining Egocentric Network Maps and Narratives: An Applied Analysis of Qualitative Network Map Interviews," Sociological Research Online, , vol. 21(2), pages 152-164, May.
    8. Read, Laura & Madani, Kaveh & Mokhtari, Soroush & Hanks, Catherine, 2017. "Stakeholder-driven multi-attribute analysis for energy project selection under uncertainty," Energy, Elsevier, vol. 119(C), pages 744-753.
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