2016
DOI: 10.1016/j.egypro.2016.11.119
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Influence of Street Canyon's Microclimate on the Energy Demand for Space Cooling and Heating of Buildings

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Cited by 16 publications
(6 citation statements)
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“…Okeil [28] introduced the residential solar block-a hypothetical building form-that outperforms linear and conventional block typologies by maximising winter but minimising summer solar radiation as a strategy for minimising heating and cooling demands, respectively. Space cooling demands for stand-alone buildings were compared to that of buildings within a street canyon configuration in Allegrini et al [29] and Vallati et al [30]. Both studies have shown that the latter requires less cooling demand than stand-alone buildings.…”
Section: Urban Geometry and Energy Consumptionmentioning
confidence: 99%
“…Okeil [28] introduced the residential solar block-a hypothetical building form-that outperforms linear and conventional block typologies by maximising winter but minimising summer solar radiation as a strategy for minimising heating and cooling demands, respectively. Space cooling demands for stand-alone buildings were compared to that of buildings within a street canyon configuration in Allegrini et al [29] and Vallati et al [30]. Both studies have shown that the latter requires less cooling demand than stand-alone buildings.…”
Section: Urban Geometry and Energy Consumptionmentioning
confidence: 99%
“…The already existing energy models and tools are able to simulate building consumption at an urban scale by assembling different sub-models [9]. However, these energy models only consider a few of the variables that actually influence the energy consumption of buildings at the urban scale [10], such as the presence of greenery [11], the albedo [12], the canyon effect [13], or the local climate conditions [14]. Indeed, designing these models at an urban scale is a complex task, since the available data usually lack some building-scale details; there is the need to make the right trade-off between model precision and the management of large amounts of data at different scales [15].…”
Section: Introductionmentioning
confidence: 99%
“…Figure13. Comparison between simulated and measured typical daily thermal consumptions, distinguishing ach = 0.5 h −1 (in orange), ach = 0.62 h −1 during the daytime, ach = 0.3 h −1 during the nighttime (in grey), and a variable ach with window openings (in blue).…”
mentioning
confidence: 99%
“…Further, the heat created by the inhabitants, equipment, and lights contribute to the overall building cooling load. External loads are caused by heat transfer through the envelope, whereas the internal loads are caused by various factors such as equipment heat and the heat generated by human activities among others [14,15]. The exterior-to-interior load ratio depends on the type of building, site environment and the design.…”
Section: Numerical Modelcooling Load Calculation Methodsmentioning
confidence: 99%