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Projecting Saudi Sectoral Electricity Demand in 2030 Using a Computable General Equilibrium Model

Author

Listed:
  • Salaheddine Soummane
  • Frederic Ghersi

    (King Abdullah Petroleum Studies and Research Center)

Abstract

Projecting future demand for electricity is central to power sector planning, as these projections inform capacity investment requirements and related infrastructure expansions. Electricity is not currently economically storable in large volumes. Thus, the underlying drivers of electricity demand and potential market shifts must be carefully considered to minimize power system costs.

Suggested Citation

  • Salaheddine Soummane & Frederic Ghersi, 2021. "Projecting Saudi Sectoral Electricity Demand in 2030 Using a Computable General Equilibrium Model," Discussion Papers ks--2021-dp012, King Abdullah Petroleum Studies and Research Center.
  • Handle: RePEc:prc:dpaper:ks--2021-dp012
    DOI: 10.30573/KS--2021-DP012
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    File URL: https://www.kapsarc.org/research/publications/projecting-saudi-sectoral-electricity-demand-in-2030-using-a-computable-general-equilibrium-model/
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    2. Abdulsalam Alghamdi & Luke S. Blunden & Majbaul Alam & AbuBakr S. Bahaj & Patrick A. B. James, 2025. "Evaluating the Opportunities and Challenges of Domestic PV Installation in Saudi Arabia Based on Field Deployment in Jeddah," Energies, MDPI, vol. 18(11), pages 1-22, May.
    3. Shahid, Muhammad & Ali, Amjad & Qadir, Sikandar Abdul & Islam, Md Tasbirul, 2025. "Empowering Saudi Arabia's sustainable energy future: A LEAP-Based approach for balancing energy supply and demand," Utilities Policy, Elsevier, vol. 95(C).
    4. Ibrahim Khalil Almadani & Ibrahim Sufian Osman & Nasir Ghazi Hariri, 2022. "In-Depth Assessment and Optimized Actuation Method of a Novel Solar-Driven Thermomechanical Actuator via Shape Memory Alloy," Energies, MDPI, vol. 15(10), pages 1-23, May.
    5. Jawed Mustafa & Fahad Awjah Almehmadi & Saeed Alqaed & Mohsen Sharifpur, 2022. "Building a Sustainable Energy Community: Design and Integrate Variable Renewable Energy Systems for Rural Communities," Sustainability, MDPI, vol. 14(21), pages 1-21, October.
    6. Salma Hamad Almuhaini & Nahid Sultana, 2023. "Bayesian-Optimization-Based Long Short-Term Memory (LSTM) Super Learner Approach for Modeling Long-Term Electricity Consumption," Sustainability, MDPI, vol. 15(18), pages 1-23, September.

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