Volume 9, Issue 2 (2019)
Naqshejahan 2019, 9(2): 117-123 |
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Moulaii M, Pilechiha P, Shadanfar A. Optimization of Window Proportions with an Approach to Reducing Energy Consumption in Office Buildings. Naqshejahan 2019; 9 (2) :117-123
URL: http://bsnt.modares.ac.ir/article-2-34001-en.html
URL: http://bsnt.modares.ac.ir/article-2-34001-en.html
1- Architecture Department, Art & Architecture Faculty, Bu-Ali Sina University, Hamedan, Iran
2- Architecture Department, Kosar Institute of Higher Education, Qazvin, Iran ,p.pilechiha@modares.ac.ir
3- Architecture Department, Kosar Institute of Higher Education, Qazvin, Iran
2- Architecture Department, Kosar Institute of Higher Education, Qazvin, Iran ,
3- Architecture Department, Kosar Institute of Higher Education, Qazvin, Iran
Abstract: (7041 Views)
Aims: Optimizing energy consumption in buildings, which includes a large part of the total energy consumed in the country, is very important. The window is also part of the interface inside and outside the building. The purpose of this research is to optimize the opening in the office in Tehran in terms of obtaining enough daylight and reducing energy consumption.
Methods: Simulation and optimization of the window performed parametrically in the Grasshopper and analysis of the objectives using the Honeybee and Ladybug plugins. The spatial Daylight Autonomy (sDA) and the Energy Use Intensity (EUI) calculated for proportions and varied window positions in eight variable directions.
Findings: The windows on the eastern north rotation and later in the east rotation had the best results. The window to wall ratio was 20% to 28%, with an average length of 6.53 and 0.9 meters, respectively, for the research model, the most ideal response. The distance between the windows to wal and the sillheight were respectively 0.65 and 2.22 meters.
Conclusion: Using modern simulation techniques enables building designers to have more intelligent choices in design with scientific approaches. The repeatable framework presented in this study can be used for buildings with different user positions or proportions, and ultimately enable designers to play an effective role in sustainable development by increasing their design productivity.
Methods: Simulation and optimization of the window performed parametrically in the Grasshopper and analysis of the objectives using the Honeybee and Ladybug plugins. The spatial Daylight Autonomy (sDA) and the Energy Use Intensity (EUI) calculated for proportions and varied window positions in eight variable directions.
Findings: The windows on the eastern north rotation and later in the east rotation had the best results. The window to wall ratio was 20% to 28%, with an average length of 6.53 and 0.9 meters, respectively, for the research model, the most ideal response. The distance between the windows to wal and the sillheight were respectively 0.65 and 2.22 meters.
Conclusion: Using modern simulation techniques enables building designers to have more intelligent choices in design with scientific approaches. The repeatable framework presented in this study can be used for buildings with different user positions or proportions, and ultimately enable designers to play an effective role in sustainable development by increasing their design productivity.
Keywords: window, parametric design, optimum level, natural light, day light, reducing energy consumption
Article Type: Original Research |
Subject:
Highperformance Architecture
Received: 2019/06/18 | Accepted: 2019/07/6 | Published: 2019/09/21
Received: 2019/06/18 | Accepted: 2019/07/6 | Published: 2019/09/21
References
1. Farhanieh B, Sattari S. Simulation of energy saving in Iranian buildings using integrative modelling for insulation. Renew Energy. 2006;31(4):417-25. [DOI:10.1016/j.renene.2005.04.004 Add to Citavi project by DOI]
2. Fasi MA, Budaiwi IM. Energy performance of windows in office buildings considering daylight integration and visual comfort in hot climates. Energy Build. 2015;108:307-16. [DOI:10.1016/j.enbuild.2015.09.024 Add to Citavi project by DOI]
3. Galatioto A, Beccali M. Aspects and issues of daylighting assessment: a review study. Renew Sustain Energy Rev. 2016;66;852-60. [DOI:10.1016/j.rser.2016.08.018 Add to Citavi project by DOI]
4. Nabil A, Mardaljevic J. Useful daylight illuminances: a replacement for daylight factors. Energy Build. 2006;38(7):905-13. [DOI:10.1016/j.enbuild.2006.03.013 Add to Citavi project by DOI]
5. Yu X, Su Y. Daylight availability assessment and its potential energy saving estimation-A literature review. Renew Sustain Energy Rev. 2015;52:494-503. [DOI:10.1016/j.rser.2015.07.142 Add to Citavi project by DOI]
6. Shahbazi M, Bemanian MR, Saremi HR. Analysis of effective key factors in adaptability of a building in the future with an emphasis on flexibility in historical buildings (case study: Bu-Ali of Hamadan). Space Ontol Int J. 2017;6(1):69-78. [link]
7. Reinhart CF, Mardaljevic J, Rogers Z. Dynamic daylight performance metrics for sustainable building design. Leukos. 2006;3(1):7-31. [DOI:10.1582/LEUKOS.2006.03.01.001 Add to Citavi project by DOI]
8. Reinhart CF, Weissman DA. The daylit area-Correlating architectural student assessments with current and emerging daylight availability metrics. Build Environ. 2012;50:155-64. [DOI:10.1016/j.buildenv.2011.10.024 Add to Citavi project by DOI]
9. Heschong L, Wymelenberg V, Andersen M, et al. Approved method: IES spatial Daylight autonomy (sDA) and annual sunlight exposure (ASE). New York: Illuminating Engineering Society of North America; 2012. [link]
10. Nabil A, Mardaljevic J. Useful daylight illuminances: A replacement for daylight factors. Energy Build. 2006;38(7):905-13. [DOI:10.1016/j.enbuild.2006.03.013 Add to Citavi project by DOI]
11. Chung W. Review of building energy-use performance benchmarking methodologies. Appl Energy. 2011;88(5):1470-9. [DOI:10.1016/j.apenergy.2010.11.022 Add to Citavi project by DOI]
12. Li DHW, Lam JC. An investigation of daylighting performance and energy saving in a daylit corridor. Energy Build. 2003;35(4):365-73. [DOI:10.1016/S0378-7788(02)00107-X Add to Citavi project by DOI]
13. Reinhart C. Daylighting handbook: fundamentals, designing with the sun. United States: Christoph Reinhart; 2014. [link]
14. Abdou OA. Effects of luminous environment on worker productivity in building spaces. J Arch Eng. 1997;3(3):124-32. [DOI:10.1061/(ASCE)1076-0431(1997)3:3(124) Add to Citavi project by DOI]
15. Ochoa CE, Aries MBC, van Loenen EJ, HensenJLM. Considerations on design optimization criteria for windows providing low energy consumption and high visual comfort. Appl Energy. 2012;95:238-45. [DOI:10.1016/j.apenergy.2012.02.042 Add to Citavi project by DOI]
16. Li DHW, Lam TNT, Wong SL, Tsang KW. Lighting and cooling energy consumption in an open-plan office using solar film coating. Energy. 2008;33(8):1288-97. [DOI:10.1016/j.energy.2008.03.002 Add to Citavi project by DOI]
17. Li DHW. A review of daylight illuminance determinations and energy implications. Appl Energy. 2010;87(7):2109-18. [DOI:10.1016/j.apenergy.2010.03.004 Add to Citavi project by DOI]
18. Ghisi E, Tinker JA. An ideal window area concept for energy efficient integration of daylight and artificial light in buildings. Build Environ. 2005;40(1):51-61. [DOI:10.1016/j.buildenv.2004.04.004 Add to Citavi project by DOI]
19. Galasiu AD, Atif MR, MacDonald RA. Impact of window blinds on daylight-linked dimming and automatic on/off lighting controls. Sol Energy. 2004;76(5):523-44. [DOI:10.1016/j.solener.2003.12.007 Add to Citavi project by DOI]
20. Baetens R, Jelle BP, Gustavsen A. Properties, requirements and possibilities of smart windows for dynamic daylight and solar energy control in buildings: a state-of-the-art review. Sol Energy Mater Sol Cells. 2010;94(2):87-105. [DOI:10.1016/j.solmat.2009.08.021 Add to Citavi project by DOI]
21. Ghisi E, Tinker J, editors. Optimising energy consumption in offices as a function of window area and room size. In: Proceedings of the 7th International IBPSA Conference; 2001 Aug 13-15; Rio de Janeiro, Brazil. Rome: Building Simulation; 2001. p. 1307-14. [link]
22. Almeida AM, Martins AG. Efficient lighting in buildings: The lack of legislation in Portugal. Energy Policy. 2014;67:82-6. [DOI:10.1016/j.enpol.2013.11.031 Add to Citavi project by DOI]
23. Shekari S, Gholmohammadi R. Estimation of" daylight autonomy" and" useful daylight illuminances" for industrial parks of Tehran. Iran Occup Health. 2010;6(4):29-37. [Persian] [link]
24. Azadeh A, Ghaderi SF, Sohrabkhani S. A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran. Energy Policy. 2008;36(7):2637-44. [DOI:10.1016/j.enpol.2008.02.035 Add to Citavi project by DOI]
25. Bokel RM. The effect of window position and window size on the energy demand for heating, cooling and electric lighting. Build Simul. 2007:117-21. [link]
26. Heschong L, Wright RL, Okura S. Daylighting impacts on human performance in school. J Illuminat Eng Soc. 2002;31(2):101-14. [DOI:10.1080/00994480.2002.10748396 Add to Citavi project by DOI]
27. Reinhart CF, Andersen M. Development and validation of a Radiance model for a translucent panel. Energy Build. 2006;38(7):890-904. [DOI:10.1016/j.enbuild.2006.03.006 Add to Citavi project by DOI]
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