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      Incorporating equivalent temperature in building cooling load prediction

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      1 , , 1 , 1 , 2 , 3
      1st International Conference on Moisture in Buildings 2021 (ICMB21)
      28-29 June 2021
      equivalent temperature, urban climate, humidity, building energy, cooling load
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            Abstract

            Buildings is accounted for a large fraction of urban energy use. Predicting building load is therefore significant for urban energy savings. The effects of sensible temperature on building energy demand have been widely studied, whereas the effects of humidity (latent temperature) is relatively less studied. The concept of equivalent temperature was adopted in this study to assess the effects of climate. A generic office building model was used to run simulations at mesoscale/local-scale. On average, latent cooling load accounted for 27.85% and 31.05% of the total cooling load in tropical and temperate cities, suggesting humidity plays a significant role in predicting building cooling demand in hot and humid areas. Moreover, equivalent temperature shows a robust correlation with the total building cooling load.

            Content

            Author and article information

            Conference
            13 May 2021
            Affiliations
            [1 ] Department of Mechanical Engineering, The University of Hong Kong
            [2 ] UCL CEGE
            [3 ] Hong Kong Observatory
            Article
            10.14293/ICMB210065
            e0903a31-8ceb-4f56-8d91-447d8679d25c
            The Author(s)

            Published under Creative Commons Attribution 4.0 International ( CC BY 4.0). Users are allowed to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material for any purpose, even commercially), as long as the authors and the publisher are explicitly identified and properly acknowledged as the original source.

            1st International Conference on Moisture in Buildings 2021
            ICMB21
            Online
            28-29 June 2021
            History
            Product

            ScienceOpen


            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            Engineering

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