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Retrofitting an Existing Office Building in the UAE Towards Achieving Low-Energy Building

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  • Maatouk Khoukhi

    (College of Engineering, United Arab Emirates University, 15551 Al Ain, UAE)

  • Abeer Fuad Darsaleh

    (College of Engineering, United Arab Emirates University, 15551 Al Ain, UAE)

  • Sara Ali

    (College of Engineering, United Arab Emirates University, 15551 Al Ain, UAE)

Abstract

Retrofitting an existing building can oftentimes be more cost-effective than building a new facility. Since buildings consume a significant amount of energy, particularly for heating and cooling, and because existing buildings comprise the largest segment of the built environment, it is important to initiate energy conservation retrofits to reduce energy consumption and the cost of heating, cooling, and lighting buildings. However, conserving energy is not the only reason for retrofitting existing buildings. The goal should be to create a high-performance building by applying an integrated, whole-building design process to the project during the planning phase that ensures that all key design objectives are met. This paper presents a real case study of the retrofitting of an existing building to achieve lower energy consumption. Indeed, most of the constructed buildings in the UAE are unsuitable for the region, which is characterized by a very harsh climate that causes massive cooling loads and energy consumption due to an appropriate selection of design parameters at the design level. In this study, a monthly computer simulation of energy consumption of an office building in Sharjah was carried out under UAE weather conditions. Several parameters, including the building orientation, heating, ventilation, and air conditioning (HVAC) system, external shading, window-to-wall ratio, and the U-values of the walls and the roof, were investigated and optimized to achieve lower energy consumption. The simulation shows that the best case is 41.7% more efficient than the real (original) case and 30.6% more than the base case. The most sensitive parameter in the retrofitting alternatives is the roof component, which affects the energy savings by 8.49%, followed by the AC system with 8.34% energy savings if well selected using the base case. Among the selected five components, a new roof structure contributed the most to the decrease in the overall energy consumption (approximately 38%). This is followed by a new HVAC system, which leads to a 37% decrease, followed by a new wall type with insulation, resulting in a 20% decrease.

Suggested Citation

  • Maatouk Khoukhi & Abeer Fuad Darsaleh & Sara Ali, 2020. "Retrofitting an Existing Office Building in the UAE Towards Achieving Low-Energy Building," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2573-:d:336521
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    References listed on IDEAS

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    1. Lindita Bande & Adalberto Guerra Cabrera & Young Ki Kim & Afshin Afshari & Mario Favalli Ragusini & Melanie Gines Cooke, 2019. "A Building Retrofit and Sensitivity Analysis in an Automatically Calibrated Model Considering the Urban Heat Island Effect in Abu Dhabi, UAE," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    2. Juan Aranda & Ignacio Zabalza & Andrea Conserva & Gema Millán, 2017. "Analysis of Energy Efficiency Measures and Retrofitting Solutions for Social Housing Buildings in Spain as a Way to Mitigate Energy Poverty," Sustainability, MDPI, vol. 9(10), pages 1-22, October.
    3. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    4. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    5. Hardi K. Abdullah & Halil Z. Alibaba, 2017. "Retrofits for Energy Efficient Office Buildings: Integration of Optimized Photovoltaics in the Form of Responsive Shading Devices," Sustainability, MDPI, vol. 9(11), pages 1-22, November.
    6. Amstalden, Roger W. & Kost, Michael & Nathani, Carsten & Imboden, Dieter M., 2007. "Economic potential of energy-efficient retrofitting in the Swiss residential building sector: The effects of policy instruments and energy price expectations," Energy Policy, Elsevier, vol. 35(3), pages 1819-1829, March.
    7. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    8. Luca Evangelisti & Claudia Guattari & Paola Gori, 2015. "Energy Retrofit Strategies for Residential Building Envelopes: An Italian Case Study of an Early-50s Building," Sustainability, MDPI, vol. 7(8), pages 1-16, August.
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    Cited by:

    1. Mamdooh Alwetaishi & Omrane Benjeddou, 2021. "Impact of Window to Wall Ratio on Energy Loads in Hot Regions: A Study of Building Energy Performance," Energies, MDPI, vol. 14(4), pages 1-15, February.
    2. Shouib Mabdeh & Hikmat Ali & Magd Al-Momani, 2022. "Life Cycle Assessment of Energy Retrofit Measures in Existing Healthcare Facility Buildings: The case of Developing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 418-431, November.
    3. Kheira Anissa Tabet Aoul & Rahma Hagi & Rahma Abdelghani & Monaya Syam & Boshra Akhozheya, 2021. "Building Envelope Thermal Defects in Existing and Under-Construction Housing in the UAE; Infrared Thermography Diagnosis and Qualitative Impacts Analysis," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    4. Amna Shibeika & Maatouk Khoukhi & Omar Al Khatib & Nouf Alzahmi & Shamma Tahnoon & Maryam Al Dhahri & Nouf Alshamsi, 2021. "Integrated Design Process for High-Performance Buildings; a Case Study from Dubai," Sustainability, MDPI, vol. 13(15), pages 1-18, July.

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