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Quantifying the domestic electricity consumption for air-conditioning due to urban heat islands in hot arid regions

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  • Radhi, Hassan
  • Sharples, Stephen

Abstract

Authoritative reports show that building electricity consumption can increase steadily once temperature values within urban regions exceed their rural values. This study first assesses the role of higher temperatures in the variation of Bahrain’s domestic electricity consumption for air-conditioning, using the cooling degree days (CDD) as a quantitative index. It then examines how this consumption is affected by urban features. The assessment is performed using established scenarios of the urban heat island (UHI), advanced statistics of building stock and data for electricity consumption. Simple regression equations are developed to predict the effects of temperature alterations on the electricity consumption. This work shows that the variation in CDD is a direct result of modifications to the urban microclimate. The annual total urban CDD value is up to 17% higher than the rural CDD value. A sharp increase of up to 10% in electricity consumption for air-conditioning occurs in urban regions from April to October. Estimates of the electricity demand for dense urban centres that are based on air temperature values measured in open areas, such as airports, can cause an error of almost 6%. The developed statistical equations can be a valuable and convenient method of quantifying the domestic electricity consumption for air-conditioning in Bahrain and other Gulf countries.

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  • 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.
  • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:371-380
    DOI: 10.1016/j.apenergy.2013.06.013
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    1. Hirano, Y. & Fujita, T., 2012. "Evaluation of the impact of the urban heat island on residential and commercial energy consumption in Tokyo," Energy, Elsevier, vol. 37(1), pages 371-383.
    2. Kikegawa, Yukihiro & Genchi, Yutaka & Kondo, Hiroaki & Hanaki, Keisuke, 2006. "Impacts of city-block-scale countermeasures against urban heat-island phenomena upon a building's energy-consumption for air-conditioning," Applied Energy, Elsevier, vol. 83(6), pages 649-668, June.
    3. 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.
    4. Kelly, Scott & Shipworth, Michelle & Shipworth, David & Gentry, Michael & Wright, Andrew & Pollitt, Michael & Crawford-Brown, Doug & Lomas, Kevin, 2013. "Predicting the diversity of internal temperatures from the English residential sector using panel methods," Applied Energy, Elsevier, vol. 102(C), pages 601-621.
    5. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    6. Al-Garni, Ahmed Z. & Zubair, Syed M. & Nizami, Javeed S., 1994. "A regression model for electric-energy-consumption forecasting in Eastern Saudi Arabia," Energy, Elsevier, vol. 19(10), pages 1043-1049.
    7. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio & Minea, Alina A., 2010. "Analysis and forecasting of nonresidential electricity consumption in Romania," Applied Energy, Elsevier, vol. 87(11), pages 3584-3590, November.
    8. Tremeac, Brice & Bousquet, Pierre & de Munck, Cecile & Pigeon, Gregoire & Masson, Valery & Marchadier, Colette & Merchat, Michele & Poeuf, Pierre & Meunier, Francis, 2012. "Influence of air conditioning management on heat island in Paris air street temperatures," Applied Energy, Elsevier, vol. 95(C), pages 102-110.
    9. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    10. Akbari, H. & Konopacki, S., 2005. "Calculating energy-saving potentials of heat-island reduction strategies," Energy Policy, Elsevier, vol. 33(6), pages 721-756, April.
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    12. Toparlar, Y. & Blocken, B. & Maiheu, B. & van Heijst, G.J.F., 2018. "Impact of urban microclimate on summertime building cooling demand: A parametric analysis for Antwerp, Belgium," Applied Energy, Elsevier, vol. 228(C), pages 852-872.
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