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Energy Modeling of a Supertall Building Using Simulated 600 m Weather File Data

  • Published : 2019.06.01

Abstract

Assessing the energy performance of supertall buildings often does not consider variations in energy consumption due to the change of environmental conditions such as temperature, pressure, and wind speed associated with differing elevations. Some modelers account for these changing conditions by using a conventional temperature lapse rate, but not many studies confirm to the appropriateness of applying it to tall buildings. This paper presents and discusses simulated annual energy consumption results from a 600 m tall skyscraper floor plate located in Dubai, UAE, assessed using ground level weather data, a conventional temperature lapse rate of $6.5^{\circ}C/km$, and more accurate simulated 600 m weather data. A typical office floorplate, with ASHRAE 90.1-2010 standards and systems applied, was evaluated using the EnergyPlus engine through the OpenStudio graphical user interface. The results presented in this paper indicate that by using ground level weather data, energy consumption at the top of the building can be overestimated by upwards of 4%. Furthermore, by only using a lapse rate, heating energy is overestimated by up to 96% due to local weather phenomenon such as temperature inversion, which can only be conveyed using simulated weather data. In addition, sizing and energy consumption of fans, which are dependent both on wind and atmospheric pressure, are not accurately captured using a temperature lapse rate. These results show that that it is important, with the ever increasing construction of supertall buildings, to be able to account for variations in climatic conditions along the height of the building. Adequately modeling these conditions using simulated weather data will help designers and engineers correctly size mechanical systems, potentially decreasing overall building energy consumption, and ensuring that these systems are able to provide the necessary indoor conditions to maintain occupant comfort levels.

Keywords

Energy modeling;Microclimate;Simulated weather;Lapse rate;Supertall buildings

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Figure 1. Three different lapse rates for Dubai summer design conditions.

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Figure 2. Three different lapse rates for Dubai winter design conditions.

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Figure 3. Wind speed variation by elevation.

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Figure 4. Typical floor axonometric view and plan indicating zonal distribution and window to wall ratio.

Table 1. Comparison of Lapse Rate Methods and Simulated Weather Data for Dubai Design Conditions

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Table 2. Internal Gains and Occupancy Density

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Table 3. Energy End Use Distribution and Totals by Climate Inputs

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References

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