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Closing the gap between wind energy targets and implementation for emerging countries

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  • Giani, Paolo
  • Tagle, Felipe
  • Genton, Marc G.
  • Castruccio, Stefano
  • Crippa, Paola

Abstract

Policymakers worldwide have set challenging sustainable energy targets to decarbonize their economy. Despite the ambitious pledges, several emerging countries still lack an actual progress towards the envisioned goals, often due to the scarcity of accurate data. Here, we propose a practical methodology for bridging the gap between the wind energy targets and their implementation. We illustrate our new methodology by focusing on Saudi Arabia, which endeavors to play a leading role in the renewable energy sector and pledges to install 16GW of wind capacity by 2030. We propose a blueprint for the optimal wind farms buildout, combining novel high-resolution model simulations, a unique set of observations, land-use restrictions and a thorough cost assessment. The most suitable technological option is selected among multiple turbine models for each potential site. Our findings suggest that Saudi Arabia is well positioned to become a role model for wind energy development within the Middle East, with 26% of the electricity demand that could be met by wind power. The average levelized cost of energy of the proposed buildout is 39 USD MWh−1, which confirms the competitiveness of wind resources in Saudi Arabia. We identify the area close to Gulf of Aqaba as the most cost-effective region for wind harvesting, with turbines characterized by moderate specific rating (350 W m−2) at relatively low hub height (75 m). The modelling framework proposed in this work can be adopted by other countries aiming to start or strengthen their wind energy portfolio.

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  • Giani, Paolo & Tagle, Felipe & Genton, Marc G. & Castruccio, Stefano & Crippa, Paola, 2020. "Closing the gap between wind energy targets and implementation for emerging countries," Applied Energy, Elsevier, vol. 269(C).
  • Handle: RePEc:eee:appene:v:269:y:2020:i:c:s0306261920305973
    DOI: 10.1016/j.apenergy.2020.115085
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    2. Dylan Harrison-Atlas & Galen Maclaurin & Eric Lantz, 2021. "Spatially-Explicit Prediction of Capacity Density Advances Geographic Characterization of Wind Power Technical Potential," Energies, MDPI, vol. 14(12), pages 1-28, June.
    3. Crippa, Paola & Alifa, Mariana & Bolster, Diogo & Genton, Marc G. & Castruccio, Stefano, 2021. "A temporal model for vertical extrapolation of wind speed and wind energy assessment," Applied Energy, Elsevier, vol. 301(C).
    4. Elshurafa, Amro M. & Alatawi, Hatem & Hasanov, Fakhri J. & Algahtani, Goblan J. & Felder, Frank A., 2022. "Cost, emission, and macroeconomic implications of diesel displacement in the Saudi agricultural sector: Options and policy insights," Energy Policy, Elsevier, vol. 168(C).
    5. Felipe Tagle & Marc G. Genton & Andrew Yip & Suleiman Mostamandi & Georgiy Stenchikov & Stefano Castruccio, 2020. "Rejoinder to the discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources," Environmetrics, John Wiley & Sons, Ltd., vol. 31(7), November.
    6. Amiri, Ali Ahmad & Wahid, Muhammad Nurdin & Al-Buraiki, Abdulrahman S. & Al-Sharafi, Abdullah, 2024. "A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS," Renewable Energy, Elsevier, vol. 236(C).
    7. Ghadah Alkhayat & Syed Hamid Hasan & Rashid Mehmood, 2023. "A Hybrid Model of Variational Mode Decomposition and Long Short-Term Memory for Next-Hour Wind Speed Forecasting in a Hot Desert Climate," Sustainability, MDPI, vol. 15(24), pages 1-39, December.
    8. Huang Huang & Stefano Castruccio & Marc G. Genton, 2022. "Forecasting high‐frequency spatio‐temporal wind power with dimensionally reduced echo state networks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(2), pages 449-466, March.
    9. Anne A. Gharaibeh & Deema A. Al-Shboul & Abdulla M. Al-Rawabdeh & Rasheed A. Jaradat, 2021. "Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization," Land, MDPI, vol. 10(5), pages 1-32, April.

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