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Residential building stock model for evaluating energy retrofit programs in Saudi Arabia

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  • Krarti, Moncef
  • Aldubyan, Mohammad
  • Williams, Eric

Abstract

This paper describes the development of a residential building stock model for the Kingdom of Saudi Arabia using an engineering bottom-up approach. The model is suitable for evaluating the impact of any energy efficiency or demand-side management program targeted for the residential building sector. The model accounts for the make-up and the characteristics of the existing Saudi housing stock using 54 prototypes representing KSA residential buildings including their type, vintage, and location. The model relies on a detailed building simulation tool to predict hourly energy consumption. The model predictions have been verified against actual reported data for energy consumption levels associated to main four Saudi regions. As an application of the building stock model, the benefits of a series of energy retrofit measures and programs are evaluated for both households and Saudi government. The analysis results clearly indicate that large-scale implementation of retrofit programs for existing KSA housing stock is cost-effective and has a wide range of economic, environmental, and social benefits. In particular, a full and targeted implementation of optimal retrofit programs can reduce the annual electricity consumption of the KSA residential sector by 50% in addition to similar decreases in carbon emissions and electricity generation capacities. The analysis results clearly indicate that for the retrofit program to be effective, the energy efficiency measures need to be tailored to the housing type, vintage, and location. Optimal sets of retrofit measures have been identified for the various categories of KSA housing stock as part of the based analysis carried out in this study.

Suggested Citation

  • Krarti, Moncef & Aldubyan, Mohammad & Williams, Eric, 2020. "Residential building stock model for evaluating energy retrofit programs in Saudi Arabia," Energy, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:energy:v:195:y:2020:i:c:s0360544220300876
    DOI: 10.1016/j.energy.2020.116980
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    3. Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Krarti, Moncef & Aldubyan, Mohammad, 2021. "Mitigation analysis of water consumption for power generation and air conditioning of residential buildings: Case study of Saudi Arabia," Applied Energy, Elsevier, vol. 290(C).
    5. Aldubyan, Mohammad & Krarti, Moncef, 2022. "Impact of stay home living on energy demand of residential buildings: Saudi Arabian case study," Energy, Elsevier, vol. 238(PA).
    6. Ahmed, Wahhaj & Asif, Muhammad, 2021. "A critical review of energy retrofitting trends in residential buildings with particular focus on the GCC countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    7. Radwan A. Almasri & Nidal H. Abu-Hamdeh & Abdullah Alajlan & Yazeed Alresheedi, 2022. "Utilizing a Domestic Water Tank to Make the Air Conditioning System in Residential Buildings More Sustainable in Hot Regions," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    8. Younghoon Kwak & Jeonga Kang & Sun-Hye Mun & Young-Sun Jeong & Jung-Ho Huh, 2020. "Development and Application of a Flexible Modeling Approach to Reference Buildings for Energy Analysis," Energies, MDPI, vol. 13(21), pages 1-22, November.
    9. Radwan A. Almasri & Abdullah A. Alardhi & Saad Dilshad, 2021. "Investigating the Impact of Integration the Saudi Code of Energy Conservation with the Solar PV Systems in Residential Buildings," Sustainability, MDPI, vol. 13(6), pages 1-30, March.
    10. Seongwon Seo & Greg Foliente, 2021. "Carbon Footprint Reduction through Residential Building Stock Retrofit: A Metro Melbourne Suburb Case Study," Energies, MDPI, vol. 14(20), pages 1-28, October.
    11. Islam, Nazrul & Irshad, Kashif & Zahir, Md Hasan & Islam, Saiful, 2021. "Numerical and experimental study on the performance of a Photovoltaic Trombe wall system with Venetian blinds," Energy, Elsevier, vol. 218(C).
    12. Marlene Ofelia Sanchez-Escobar & Julieta Noguez & Jose Martin Molina-Espinosa & Rafael Lozano-Espinosa & Genoveva Vargas-Solar, 2021. "The Contribution of Bottom-Up Energy Models to Support Policy Design of Electricity End-Use Efficiency for Residential Buildings and the Residential Sector: A Systematic Review," Energies, MDPI, vol. 14(20), pages 1-28, October.
    13. Marlene Ofelia Sanchez-Escobar & Julieta Noguez & Jose Martin Molina-Espinosa & David Escobar-Castillejos & Sergio Ruiz-Loza, 2023. "Policy Design for Electricity Efficiency: A Case Study of Bottom-Up Energy Modeling in the Residential Sector and Buildings," Energies, MDPI, vol. 16(19), pages 1-39, September.
    14. 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.
    15. Belaïd, Fateh & Massié, Camille, 2023. "The viability of energy efficiency in facilitating Saudi Arabia's journey toward net-zero emissions," Energy Economics, Elsevier, vol. 124(C).
    16. 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.
    17. Salma Hamad Almuhaini & Nahid Sultana, 2023. "Forecasting Long-Term Electricity Consumption in Saudi Arabia Based on Statistical and Machine Learning Algorithms to Enhance Electric Power Supply Management," Energies, MDPI, vol. 16(4), pages 1-28, February.

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