Parametric analysis of sunspace heating performance of building in cold climate (Case study: Sanandaj)

Subject Areas : architecture

parisa abdekhaleghi ¹ , zhale sabernezhad ² , rima fayaz ³

1 - Faculty of Architecture, Azad University, Kish International Branch
2 - Faculty of Architecture, Azad University, South Tehran Branch
3 - Faculty of Architecture and Urbanism, University of Arts, Tehran

Received: 2020-07-14 Accepted : 2022-05-19 Published : 2022-10-23

Keywords: Sunspace, Building, Cold Climate, Sanandaj city, Energy performance,

Abstract :

Increasing energy consumption in buildings has result in environmental issues and have led many researchers to explore ways to reduce fossil fuel consumption. One of the most cost-effective and logical ways to use energy resources in residential buildings is to use passive solar systems such as sunspaces.Sunspaces are passive systems that can easily be integrated into the structure of a building, whether it is under construction or already completed. The primary role of passive sunspace systems is to collect solar energy, accumulate it inside, and transfer it to other living areas. In addition, sunspaces also serve as buffer zones, protecting the indoor space from excessive heat loss.The design of building with a sunspace can be improved if the method of energy performance simulation is accompanied by optimization algorithms. Building optimization can include a variety of goals, such as energy, environmental, economic, etc. Use of passive systems in residential buildings can provide a substantial portion of passive solar heating, but the degree of efficiency of sunlight depends on numerous parameters, such as climatic parameters. In this paper, the effects of sunspaces on energy gain and reducing energy consumption are presented. The best known stationary methods, such as those used in the EN ISO 13790 standard do not yield sufficiently accurate results. Dynamic simulation methods that can determine energy needs of buildings more precisely require computer support and more time for the simulation to be performed.The energy performance of the sunspace was calculated using parametric modeling in Grasshopper software and Rhino software and energy simulation was carried out using Energyplus. Simulations were performed according to the climate of the city of Sanadaj,which is located in a cold climate area, Meteorological data considered in the model represent a meteorological year.The proposed method of performance optimization utilizes various tools and technologies including parametric design, building simulation modeling, and Genetic Algorithms. To achieve simulation goals, different models of sunspace with different dimensions and orientations in Sanandaj have been studied. Modifications of the the models included different proportions of sunspace dimensions, orientations, , and the use of different thermal insulations.The orientation, towards the south, receives the highest energy, and with a ,20 degrees rotation to the west or east, the highest amount of energy can be gained. Examination of sunspace models with 3 percentages of window-to-wall ratio: 40%, 50% and 60% showed that the 50% percent WWR is more desirable compared to other models. The highest increase in energy absorption to help reduce the heating load during the cold season occurs when the sunspace has the longest length, ie 5 meters, because in this case, the southward is increased and the desired depth is 1 meter while by reducing or increasing this amount, solar energy gain is reduced. Also, to improve the performance of the sunspace, the use of conventional thermal insulation has been investigated. Polyurethane with a thickness of 10 cm has the lowest efficiency in terms of reducing energy consumption in the sunspace, while other insulating materials with similar thichness are more effective.

References:

1. ابراهیم پور، عبدالسلام؛ و معرفت، مهدی. (1390). اصلاح روشی جهت تولید داده های اقلیمی TMY برای شهر تهران،مهندسی مکانیک مدرس، ۱۱ (2)، ۷۷-۹۱.


2. ابراهیم پور، عبدالسلام؛ و کسمایی، مرتضی. (1392).تهیه فایل‌های اقلیمی TMY برای شهرهای مهم ایران، انتشارات مرکز تحقیقات راه، مسکن و شهرسازی.


3. احمدی ندوشن، افشین و بهادری نژاد، مهدی، (1385)،کاهش انرژی برودتی و حرارتی مجتمع‌های مسکونی با استفاده از بادبزن‌های سقفی،چهاردهمین کنفرانس سالانه مهندسی مکانیک،اصفهان.


4. رحیم‌پور، آیدا؛ و رحیمی، مجتبی. (1392). اهمیت و لزوم استفاده از انرژی‌های نو در ساختمان‌های مسکونی استان کرمان و طراحی. ساختمان سبز،اولین همایش ملی انرژی‌های نو و پاک، همدان.


5. لکنر. نربرت. (1385).گرمایش، سرمایش، روشنایی رویکردهای طراحی برای معماران، (محمدعلی کی­نژاد و رحمان­آذری، مترجمان)، تبریز: انتشارات دانشگاه هنر اسلامی تبریز. (نشر اثر اصلی:2001)


6. مازریا، ادورد. (1385).معماری خورشیدی غیرفعال. (بیژن آقازاده، مترجم). تهران: نشر پیک ادبیات.


7. گیلانی، سارا؛ و محمدکاری، بهروز. (1390). بررسی عملکرد گرمایشی گلخانه‌های خورشیدی در ساختمان‌های مسکونی اقلیم سرد نمونه موردی: شهر اردبیل.مهندسی مکانیک مدرس، ۱۱ (۲)، ۱۴۷-۱۵۷.


8. Alzoubi, H. H., & Malkawi, A. T. (2015). The optimal utilization of solar energy in residential buildings in light of the Jordanian building regulations. Sustainable Cities and Society, 14, 441-448.https://doi.org/10.1016/j.scs.2014.06.001.


9. Attia, S., Hamdy, M., O’Brien, W., & Carlucci, S. (2013). Computational optimisation for zero energy buildings design interviews results with twenty eight international expert. In Proceedings of the 13th Conference of International Building Performance Simulation Association.


10. Berardi, U. (2017). A cross-country comparison of the building energy consumptions and their trends. Resources, Conservation and Recycling, 123, 230-241.‏


11. Carlucci, S., Cattarin, G., Causone, F., & Pagliano, L. (2015). Multi-objective optimization of a nearly zero-energy building based on thermal and visual discomfort minimization using a non-dominated sorting genetic algorithm (NSGA-II). Energy and Buildings, 104, 378-394.


12. Coakley, D., Raftery, P., & Molloy, P. (2012). Calibration of whole building energy simulation models: detailed case study of a naturally ventilated building using hourly measured data. Building Simulation and Optimization, 57-64.


13. Eskin, N., & Türkmen, H. (2008). Analysis of annual heating and cooling energy requirements for office buildings in different climates in Turkey. Energy and buildings, 40(5), 763-773.


14. Chiesa, G., Simonetti, M., & Ballada, G. (2017). Potential of attached sunspaces in winter season comparing different technological choices in Central and Southern Europe. Energy and Buildings, 138, 377-395.


15. Godoy-Shimizu, D., Steadman, P., Hamilton, I., Donn, M., Evans, S., Moreno, G., & Shayesteh, H. (2018). Energy use and height in office buildings. Building Research & Information, 46(8), 845-863.


16. International Energy Agency, Energy Access Outlook 2017, Retrieved October 2016, from 


17. Jørgensen, O. B., & Hendriksen, O. J. (2000). Glazed balconies and sun spaces–energy savers or energy wasters. In Proceedings of the Third ISES Europe Solar Congress (Eurosun2000), Copenhagen, Denmark, 19-22.


18. Moore, F. (1993). Environmental control systems: Heating, cooling, lighting. architecture and urban planninig series. New York: McGraw-Hill.


19. Neto, A. H., & Fiorelli, F. A. S. (2008). Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption. Energy and buildings, 40(12), 2169-2176.‏


20. Raji, B., Tenpierik, M. J., & Van den Dobbelsteen, A. (2017). Early-stage design considerations for the energy-efficiency of high-rise office buildings. Sustainability, 9(4), 1-28.


21. Taleghani, M., Tenpierik, M. J., & Van den Dobbelsteen, A. A. J. F. (2012). The effect of different transitional spaces on thermal comfort and energy consumption of residential buildings. In 7th Windsor Conference 2012: The changing context of comfort in an unpredictable world, Windsor, UK, 12-15 April 2012.


22. Ulpiani, G., Giuliani, D., Romagnoli, A., & di Perna, C. (2017). Experimental monitoring of a sunspace applied to a NZEB mock-up: Assessing and comparing the energy benefits of different configurations. Energy and Buildings, 152, 194-215.


23. Yu, J., Yang, C., & Tian, L. (2008). Low-energy envelope design of residential building in hot summer and cold winter zone in China. Energy and Buildings, 40(8), 1536-1546.‏


24. ZEDFactory (2016), Retrieved April 2022