Session: 02-05 Innovations for Sustainably Built Environments
Paper Number: 107814
107814 - Urban Scale Cooling Load Prediction of High-Rise Buildings in a Hot and Arid Climate
Urban scale cooling load prediction for high-rise buildings in a hot and arid climate
Authors:
Omar Ahmed 1, Majd Moujahed 1, Nurettin Sezer 2, Liangzhu (Leon) Wang 1, Ibrahim Galal Hassan 2,*
1 = Centre for Zero Energy Building Studies, Department of Building, Civil and Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, Quebec, H3G 1M8, Canada
2 = Mechanical Engineering Program, Texas A&M University at Qatar, Engineering Building, Education City, Al Rayyan, P.O. Box 23874, Doha, Qatar
* = Corresponding author details, ibrahim.hassan@qatar.tamu.edu
Aim and Approach:
This study employs an archetype-based approach for cooling load prediction using a case study of high-rise buildings in the Marina district of Lusail City, Qatar. Since the Marina district is a newly built district, the building typology and geometric characteristics were considered the main criteria for the selection of representative archetypes of the district. Three high-rise building archetypes were developed using EnergyPlus to represent the three building typologies available in the district: Residential, Commercial, and Mixed-use. Required data for the input parameters were collected from various sources such as the GSAS-2 star rating guideline, considering that it is the minimum requirement in the region, ASHRAE 90.1, and ASHRAE 62.1 standards, along with user surveys when available. Representative building energy models were created for each of the studied archetypes. Detailed cooling profiles for these three building archetypes enable aggregating the loads to obtain the urban scale cooling profile at various time resolutions.
Scientific Innovation and Relevance:
In this study, realistic and detailed cooling load profiles of different temporal scales are presented for buildings in the hot and arid climate of Qatar. These cooling load profiles can inform the design and operation process of district cooling facilities, investigate the energy-saving potential of buildings, and aid in the development of cost allocation or billing strategies for end users without the need for zone-level submeters. Furthermore, the building archetypes produced in this study are applicable beyond the scope of the Marina district, elsewhere in regions with hot and humid climates and similar building characteristics. This study also aids in the establishment of a representative building archetype library for regions with hot and arid climates.
Preliminary Results and Conclusion:
Preliminary results are obtained for the main components of the hourly cooling load profile for a commercial building archetype on a typical weekend and weekday. Cooling the ventilation air from the outside temperature to the setpoint temperature represents the most significant factor contributing to the buildings’ cooling load while building lighting contributes the least to the cooling load. The variation in cooling load is also apparent between weekdays and weekends, mainly caused by the difference in operating schedules between both days. The ventilation air cooling accounts for nearly half of the difference in cooling load between the two days while building infiltration and window heat gain seem to be the most unchanged parameters when comparing weekdays to weekends. The next step of this study will be the validation of building cooling load profiles at different scales with available benchmarks and measured data to assess the performance of the developed archetype models.
Presenting Author: Omar Ahmed Concordia University
Presenting Author Biography: Omar Is a M.Sc. student in the department of Building, Civil and Environmental engineering, Concordia university, Canada with current research focused on urban scale building energy modeling and optimizing the accuracy of UBEMs.
Urban Scale Cooling Load Prediction of High-Rise Buildings in a Hot and Arid Climate
Paper Type
Technical Paper Publication