Determining the Optimum Geometrical Design Parameters of Windows in Commercial Buildings: Comparison between Humid Subtropical and Humid Continental Climate Zones in the United States
Publication: Journal of Architectural Engineering
Volume 24, Issue 4
Abstract
Several studies indicate that the building sector has the highest contribution to world energy consumption. Also, it is predicted that the energy demand in commercial buildings will increase to 1.2% per annum from 2006 to 2030 due to population and economic growth. This has forced governments to focus on a reduction in the energy costs of commercial buildings by promoting the construction of new buildings and retrofitting existing ones. Many different parameters, such as building orientation, thermal mass, and building-envelope elements, affect building energy performance. The building envelope, as the mediator between buildings’ outside and inside conditions, plays a critical role in reducing energy consumption. Windows, as the eyes of the building, are the most sensitive elements of the building envelope and should be given considerable attention. Due to the number of passive-design variables for windows (e.g., window-to-wall ratio, shading, reveal, and aspect ratio) involved in the design process, selecting suitable design parameters for windows is always a major challenge for designers. This article presents a simulation-based optimization model that is used during the early stages of design to identify the optimum window design parameters to minimize the energy consumption of office buildings. The proposed optimization model employs a harmony search algorithm coupled with EnergyPlus 8.4.0 software to identify the optimum or near-optimum design parameters. Additionally, a case study of an office building in two different climate regions is presented to illustrate the application of this model. The results show that by identifying the optimum window design parameters, the total energy consumption of the office building model can be reduced by 37%. In addition, the computational tool can be valuable for architects and engineers in determining the optimum design parameters at the early stages of the design.
Get full access to this article
View all available purchase options and get full access to this article.
References
Acosta, I., M. Á. Campano, and J. F. Molina. 2016. “Window design in architecture: Analysis of energy savings for lighting and visual comfort in residential spaces.” Appl. Energy 168: 493–506. https://doi.org/10.1016/j.apenergy.2016.02.005.
Amaral, A. R., E. Rodrigues, A. R. Gaspar, and Á. Gomes. 2016. “A thermal performance parametric study of window type, orientation, size and shadowing effect.” Sustainable Cities Soc. 26: 456–465. https://doi.org/10.1016/j.scs.2016.05.014.
Architecture 2030. 2010. “The 2030 Challenge”. http://architecture2030.org/2030_challenges/2030-challenge/.
Asadi, S. 2014. “A multi-objective harmony-search algorithm for building life-cycle energy optimization.” In Proc., 2014 Construction Research Congress, 484–493. Reston, VA: ASCE.
Charalambides, J., and J. Wright. 2013. “Effect of early solar energy gain according to building size, building openings, aspect ratio, solar azimuth, and latitude.” J. Archit. Eng. 19 (3): 209–216. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000129.
DOE (US Department of Energy). (n.d.). “ENERGY.GOV.” https://www.energy.gov/ (October 10, 2017).
DOE (US Department of Energy). 2010. EnergyPlus engineering reference: The reference to EnergyPlus calculations. Washington, DC: DOE.
Fesanghary, M., S. Asadi, and Z. W. Geem. 2012. “Design of low-emission and energy-efficient residential buildings using a multi-objective optimization algorithm.” Build. Environ. 49: 245–250. https://doi.org/10.1016/j.buildenv.2011.09.030.
Geem, Z. W., J. H. Kim, and G. V. Loganathan. 2001. “A new heuristic optimization algorithm: Harmony search.” Simul. 76 (2): 60–68. https://doi.org/10.1177/003754970107600201.
Geem, Z. W., J. H. Kim, and G. V. Loganathan. 2002. “Harmony search optimization: Application to pipe network design.” Int. J. Modell. Simul. 22 (2): 125–133. https://doi.org/10.1080/02286203.2002.11442233.
Ghisi, E., and J. A. Tinker. 2005. “An ideal window area concept for energy efficient integration of daylight and artificial light in buildings.” Build. Environ. 40 (1): 51–61. https://doi.org/10.1016/j.buildenv.2004.04.004.
Goia, F. 2016. “Search for the optimal window-to-wall ratio in office buildings in different European climates and the implications on total energy saving potential.” Solar Energy 132: 467–492. https://doi.org/10.1016/j.solener.2016.03.031.
Hassanain, M. A., and E. L. Harkness. 1998. “Priorities in building envelope design.” J. Archit. Eng. 4 (2): 47–51. https://doi.org/10.1061/(ASCE)1076-0431(1998)4:2(47).
Inanici, M. N., and F. N. Demirbilek. 2000. “Thermal performance optimization of building aspect ratio and south window size in five cities having different climatic characteristics of Turkey.” Build. Environ. 35 (1): 41–52. https://doi.org/10.1016/S0360-1323(99)00002-5.
Mahdavi, A., A. Mohammadi, E. Kabir, and L. Lambeva. 2008. “Occupants’ operation of lighting and shading systems in office buildings.” J. Build. Perform. Simul. 1 (1): 57–65. https://doi.org/10.1080/19401490801906502.
McDonald, S. S., and S. Chakradhar. 2017. “Energy-efficient commercial complex in Kathmandu, Nepal: Integrating energy simulations into the design process.” J. Archit. Eng. 23 (2): C4017001. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000239.
Moeck, M., and Y. J. Yoon. 2004. “Green buildings and potential electric light energy savings.” J. Archit. Eng. 10 (4): 143–159. https://doi.org/10.1061/(ASCE)1076-0431(2004)10:4(143).
Motuziene, V., and E. S. Juodis. 2010. “Simulation based complex energy assessment of office building fenestration.” J. Civ. Eng. Manage. 16 (3): 345–351. https://doi.org/10.3846/jcem.2010.39.
Passe, U., and R. Nelson. 2013. “Constructing energy efficiency: Rethinking and redesigning the architectural detail.” J. Archit. Eng. 19 (3): 193–203. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000108.
Su, X., and X. Zhang. 2010. “Environmental performance optimization of window–wall ratio for different window type in hot summer and cold winter zone in China based on life cycle assessment.” Energy Build. 42 (2): 198–202. https://doi.org/10.1016/j.enbuild.2009.08.015.
Susorova, I., M. Tabibzadeh, A. Rahman, H. L. Clack, and M. Elnimeiri. 2013. “The effect of geometry factors on fenestration energy performance and energy savings in office buildings.” Energy Build. 57: 6–13. https://doi.org/10.1016/j.enbuild.2012.10.035.
Tzempelikos, A. 2012. “Development and implementation of lighting and shading control algorithms in an airport building.” J. Archit. Eng. 18 (3): 242–250. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000062.
Tzempelikos, A., and A. K. Athienitis. 2007. “The impact of shading design and control on building cooling and lighting demand.” Solar Energy 81 (3): 369–382. https://doi.org/10.1016/j.solener.2006.06.015.
Vanhoutteghem, L., G. C. J. Skarning, C. A. Hviid, and S. Svendsen. 2015. “Impact of façade window design on energy, daylighting and thermal comfort in nearly zero-energy houses.” Energy Build. 102: 149–156. https://doi.org/10.1016/j.enbuild.2015.05.018.
Yang, X.-S. 2009. “Harmony search as a metaheuristic algorithm.” Chap. 1 in Music-inspired harmony search algorithm, 1–14. Berlin: Springer.
Information & Authors
Information
Published In
Copyright
© 2018 American Society of Civil Engineers.
History
Received: Aug 29, 2017
Accepted: May 1, 2018
Published online: Aug 8, 2018
Published in print: Dec 1, 2018
Discussion open until: Jan 8, 2019
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.