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Development of benchmark models for the Egyptian residential buildings sector

Author

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  • Attia, Shady
  • Evrard, Arnaud
  • Gratia, Elisabeth

Abstract

The aim of this study is to develop representative simulation building energy data sets and benchmark models for the Egyptian residential sector. This study reports the results of a recent field survey for residential apartment buildings in Egypt. Two building performance simulation models are created reflecting the average energy consumption characteristics of air-conditioned residential apartments in Alexandria, Cairo and Asyut. Aiming for future evaluation of the cost and energy affects of the new Egyptian energy standard this study established two detailed models describing the energy use profiles for air-conditioners, lighting, domestic hot water and appliances in respect to buildings layout and construction. Using EnergyPlus simulation tool the collected surveyed data was used as input for two building simulation models. The simulation models were verified against the apartment characteristic found in the survey. This paper presents details of the building models including the energy use patterns and profiles created for this study.

Suggested Citation

  • Attia, Shady & Evrard, Arnaud & Gratia, Elisabeth, 2012. "Development of benchmark models for the Egyptian residential buildings sector," Applied Energy, Elsevier, vol. 94(C), pages 270-284.
  • Handle: RePEc:eee:appene:v:94:y:2012:i:c:p:270-284
    DOI: 10.1016/j.apenergy.2012.01.065
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    References listed on IDEAS

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    1. Lam, Joseph C. & Wan, Kevin K.W. & Wong, S.L. & Lam, Tony N.T., 2010. "Long-term trends of heat stress and energy use implications in subtropical climates," Applied Energy, Elsevier, vol. 87(2), pages 608-612, February.
    2. Lam, Joseph C., 1996. "An analysis of residential sector energy use in Hong Kong," Energy, Elsevier, vol. 21(1), pages 1-8.
    3. Abdel-Aal, R.E. & Al-Garni, A.Z. & Al-Nassar, Y.N., 1997. "Modelling and forecasting monthly electric energy consumption in eastern Saudi Arabia using abductive networks," Energy, Elsevier, vol. 22(9), pages 911-921.
    4. Murata, Akinobu & Kondou, Yasuhiko & Hailin, Mu & Weisheng, Zhou, 2008. "Electricity demand in the Chinese urban household-sector," Applied Energy, Elsevier, vol. 85(12), pages 1113-1125, December.
    5. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    6. Pachauri, Shonali, 2004. "An analysis of cross-sectional variations in total household energy requirements in India using micro survey data," Energy Policy, Elsevier, vol. 32(15), pages 1723-1735, October.
    7. Ranjan, Manish & Jain, V.K., 1999. "Modelling of electrical energy consumption in Delhi," Energy, Elsevier, vol. 24(4), pages 351-361.
    8. Bojic, Milorad & Nikolic, Novak & Nikolic, Danijela & Skerlic, Jasmina & Miletic, Ivan, 2011. "Toward a positive-net-energy residential building in Serbian conditions," Applied Energy, Elsevier, vol. 88(7), pages 2407-2419, July.
    9. Abosedra, Salah & Dah, Abdallah & Ghosh, Sajal, 2009. "Electricity consumption and economic growth, the case of Lebanon," Applied Energy, Elsevier, vol. 86(4), pages 429-432, April.
    10. Mohamed, Zaid & Bodger, Pat, 2005. "Forecasting electricity consumption in New Zealand using economic and demographic variables," Energy, Elsevier, vol. 30(10), pages 1833-1843.
    11. Xiaohua, Wang & Zhenming, Feng, 1997. "Rural household energy consumption in Yangzhong county of Jiangsu province in China," Energy, Elsevier, vol. 22(12), pages 1159-1162.
    12. Mansouri, Iman & Newborough, Marcus & Probert, Douglas, 1996. "Energy consumption in UK households: Impact of domestic electrical appliances," Applied Energy, Elsevier, vol. 54(3), pages 211-285, July.
    13. Azadeh, A. & Ghaderi, S.F. & Sohrabkhani, S., 2008. "A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran," Energy Policy, Elsevier, vol. 36(7), pages 2637-2644, July.
    14. Sivak, Michael, 2009. "Potential energy demand for cooling in the 50 largest metropolitan areas of the world: Implications for developing countries," Energy Policy, Elsevier, vol. 37(4), pages 1382-1384, April.
    15. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    16. Aydinalp, Merih & Ismet Ugursal, V. & Fung, Alan S., 2002. "Modeling of the appliance, lighting, and space-cooling energy consumptions in the residential sector using neural networks," Applied Energy, Elsevier, vol. 71(2), pages 87-110, February.
    17. Sözen, Adnan & Arcaklioglu, Erol & Özkaymak, Mehmet, 2005. "Turkey's net energy consumption," Applied Energy, Elsevier, vol. 81(2), pages 209-221, June.
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    Cited by:

    1. Gaiser, Kyle & Stroeve, Pieter, 2014. "The impact of scheduling appliances and rate structure on bill savings for net-zero energy communities: Application to West Village," Applied Energy, Elsevier, vol. 113(C), pages 1586-1595.
    2. Radhi, Hassan & Sharples, Stephen, 2013. "Quantifying the domestic electricity consumption for air-conditioning due to urban heat islands in hot arid regions," Applied Energy, Elsevier, vol. 112(C), pages 371-380.
    3. Brandão de Vasconcelos, Ana & Pinheiro, Manuel Duarte & Manso, Armando & Cabaço, António, 2015. "A Portuguese approach to define reference buildings for cost-optimal methodologies," Applied Energy, Elsevier, vol. 140(C), pages 316-328.
    4. Corgnati, Stefano Paolo & Fabrizio, Enrico & Filippi, Marco & Monetti, Valentina, 2013. "Reference buildings for cost optimal analysis: Method of definition and application," Applied Energy, Elsevier, vol. 102(C), pages 983-993.
    5. Yang, Tian-Jian & Zhang, Yue-Jun & Tang, Su & Zhang, Jing, 2016. "How to assess and manage energy performance of numerous telecommunication base stations: Evidence in China," Applied Energy, Elsevier, vol. 164(C), pages 436-445.
    6. Szalay, Zsuzsa & Zöld, András, 2014. "Definition of nearly zero-energy building requirements based on a large building sample," Energy Policy, Elsevier, vol. 74(C), pages 510-521.
    7. Filogamo, Luana & Peri, Giorgia & Rizzo, Gianfranco & Giaccone, Antonino, 2014. "On the classification of large residential buildings stocks by sample typologies for energy planning purposes," Applied Energy, Elsevier, vol. 135(C), pages 825-835.
    8. Arumägi, Endrik & Kalamees, Targo, 2014. "Analysis of energy economic renovation for historic wooden apartment buildings in cold climates," Applied Energy, Elsevier, vol. 115(C), pages 540-548.

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