ارائه مدل بهینه سازی ساختمان جهت مقابله با اثرات منفی تغییرات اقلیمی در جهت کاهش مصرف انرژی
محورهای موضوعی : معماری و شهرسازی
اردا زارعی
1
(
گروه مهندسي عمران، واﺣﺪ ﺗﺒﺮﻳﺰ، داﻧﺸﮕﺎه آزاد اﺳﻼﻣﻲ، ﺗﺒﺮﻳﺰ، ایران.
)
سینا فرد مرادی نیا
2
(
اﺳﺘﺎدﻳﺎر، گروه مهندسي عمران، واحد تبريز، دانشگاه آزاد اسلامي، تبریز، ايران. *(مسوول مکاتبات)
)
کلید واژه: بهینه سازی ساختمان, تغییرات اقلیمی, انرژی ساختمان, نرم افزار جی ای پلاس, بارگرمایی و سرمایی.,
چکیده مقاله :
زمینه و هدف: امروزه کلان شهر ها نقش بسیار مهمی در آلایندگی محیط زیست دارند، افزایش روزافزون جمعيـت بـا افـزایش مصـرف سوخت هاي فسيلي و منابع انرژي همراه است که این موضوع باعث افزایش انتشارات گازهاي گلخانه اي در اتمسفر ميشود. اثـرات افـزایش گازهاي گلخانه اي با بروز پدیده گلخانه اي سبب تغييـرات اقليمـي مي شود. با توجه به اتلاف زياد انرژي در ساختمان هـاي مسکونی موجـود، هدف این تحقیق انتخاب راهكار مناسب براي بهینه سازی ساختمان و كاهش مصـرف انرژی در اين بخش است. روش بررسی: در این تحقيق، در تاریخ 1/10/1398 ابتدا مقدار انرژی مصرفی سالانه یک تیپ ساختمان مسکونی 8 طبقه در تبریز با استفاده از نرم افزار انرژی پلاس شبیه سازی شد. سپس مقدار انرژی مصرفی سالانه ساختمان یاد شده با شرایط آب و هوای دو اقلیم متفاوت یزد و رشت نیز شبیه سازی شد تا میزان مصرف انرژی ساختمان در هر 3 شهر مقایسه شود. سپس با کمک نرم افزار شبیه سازی JePlus، انرژی مصرفی حالت های مختلف ساختمان (جهت گیری، موقعیت، دما، اقلیم)، درهر 3 شهر شبیه سازی شد تا رفتار ساختمان از لحاظ مصرف انرژی بررسی شود. در نهایت مقدار انرژی مصرفی گرمایشی و سرمایشی ساختمان به عنوان توابع هدف انتخاب شده و توسط نرم افزار JePlus + EA بهینه سازی انجام گرفت. يافته ها: با توجه به متغیرهای تعریف شده در ورودی نرم افزار JePlus، 432 حالت مصرف انرژی برای ساختمان به¬دست آمد. و با توجه به انتخاب انرژی مصرفی گرمایشی و سرمایشی ساختمان به عنوان توابع هدف، توسط نرم افزار JePlus + EA بهینه سازی انجام گرفت. نتایج بهینه سازی نشان داد با توجه به پارامترهای یکسان در نظر گرفته شده برای هر سه اقلیم، مصرف انرژی ساختمان در شهر رشت 16 درصد، یزد 14 درصد و تبریز 12 درصد کاهش یافته است. بحث و نتیجه گیری: بررسی نتایج این مطالعه نشان داد اگر ساختمان¬ در جهت و موقعیت صحیح با توجه به نوع اقلیم و وضعیت آب و هوا (جهت تابش خورشید، دما، رطوبت و...) احداث شود و دمای گرمایش و سرمایش داخل ساختمان در حد آسایش تنظیم گردد، مصرف انرژی ساختمان نیز درحد قابل ملاحظه ای کاهش می¬یابد؛ در نتیجه از سهم هر ساختمان در میزان انتشار گاز دی اکسید کربن در اتمسفر که اثرگذارترین گاز در تغییرات اقلیمی است، کاسته می شود.
Background and Objective: Today, metropolises play a very important role in environmental pollution, increasing population is associated with increasing consumption of fossil fuels and energy resources, which increases greenhouse gas emissions into the atmosphere. The effects of increasing greenhouse gases with the occurrence of greenhouse phenomena cause climate change. Due to the high energy loss in residential buildings, The purpose of this study is to select an appropriate solution to optimize the building and reduce energy consumption in this sector. Material and Methodology: In this research, first, the annual energy consumption of a type of 8-storey residential building in Tabriz was simulated using Energy Plus software. Then, the annual energy consumption of the building was simulated with the weather conditions of two different climates of Yazd and Rasht to compare the energy consumption of the building in all 3 cities. Then, with JePlus simulation software, the energy consumption of different building modes (orientation, position, temperature, climate) was simulated in all 3 cities to study the behavior of the building in terms of energy consumption. Finally, the amount of heating and cooling energy consumption of the building was selected as the target functions and optimized by JePlus + EA software. Findings: According to the variables defined in the input of JePlus software, 432 energy consumption modes were obtained for the building. And according to the selection of heating and cooling energy consumption of the building as target functions, optimization was done by JePlus + EA software. The optimization results showed that according to the same parameters considered for all three climates, building energy consumption in Rasht has decreased by 16%, Yazd by 14% and Tabriz by 12%. Discussion and Conclusion: The results showed that if the building is built in the right direction and position according to the type of climate and weather conditions (for sunlight, temperature, humidity, etc.) and the heating and cooling temperature inside the building is set to comfort, The energy consumption of the building is also significantly reduced As a result, the share of each building in the amount of carbon dioxide emissions into the atmosphere, which is the most effective gas in climate change, is reduced.
1. Asghari, M., Poulaei, Z and Yazdani, H., 2019. Energy analysis of building cooling load using canopies and thermal insulation in three warm, temperate and cold climates of Iran, Iranian Journal of Mechanical Engineers, 123, pp.14-24. (In Persian)
2. Irani, A and Nasrollahi, F., 2019. Study of Climate Change in the period 2080-2020, Green Architecture Quarterly, 5, 1. (In Persian)
3. Moharrami, M., Khodaverdi, P., Abbasi, Y and Sohrabi, A., 2019. A Review of the Impact of Changing Building Elements on Energy Consumption Optimization in Residential Buildings, Journal of Civil and Research, 1, pp.98-113. (In Persian)
4. Nasirzadeh, E., and Shsfiee, M., 2019. Investigating the green and environmentally friendly building approach in designing office buildings for optimization and energy storage, Architecture, 1, 6. (In Persian)
5. Rahmani, M., Shakouri, H and Kazemi, A., 2017. Presenting a Multi-Objective Optimization Model to Increase Energy Efficiency in Residential Buildings, Industrial Management, 9, 1, pp. 28-103. (In Persian)
6. Gheybi, F,. Mousavi, R and Eskandari, H., 2016. Numerical and experimental study of glass facades in office buildings in hot and dry climates, Iranian Journal of Energy, 20, 4, pp. 25-25. (In Persian)
7. Khodakarami, J and Ghobadi, P., Optimization of energy consumption in an office building equipped with an intelligent system, Journal of Energy Engineering and Management, 6, 2, pp.12-23. (In Persian)
8. Zargami, E and Adibi, E., 2016. Evaluation of Green Roof Thermal Performance in Sustainability and Optimization of Energy Consumption of Residential Buildings in Hot and Dry Climate of Iran, Architecture and Urban Planning, 4, 1. (In Persian)
9. Ebrahimpour, A and Karimi, Y., 2012. Appropriate Methods for Optimizing Energy Consumption in a University Building in Tabriz, Modares Journal of Mechanical Engineering, 12, 4, pp.91-104. (In Persian)
10. Gan, V.J.L., Wong, H.K., Tse, K.T., Cheng, Jack CP., Lo, Irene M.c and Chan, CM., 2019. Simulation-based evolutionary optimization for energy-efficient layout plan design of high-rise residential buildings. Journal of Cleaner Production, 231, pp.1375-1388.
11. Georgiou, S.G., Christodoulides, P and Kalogirou, S.A., 2019. Real-time Energy Convex Optimization via electrical storage in Buildings - A Review. Renewable Energy, 139, pp.1375-1388.
12. Kamal, R., Moloney, F., Wickramaratne, C., Narasimhan, A and Goswamib, D.Y., 2019. Strategic control and cost optimization of thermal energy storage in buildings using EnergyPlus. Applied Energy, 246, pp.77-90.
13. Dino, G.I., and Akgül, M.C., 2019. Impact of climate change on the existing residential building stock in Turkey: Ananalysis on energy use, greenhouse gas emissions and occupant comfort. Renewable Energy, 141, pp.828-846.
14. Gercek, M and Arsan, D.Z., 2019. Energy and environmental performance based decision support process for early design stages of residential buildings. Sustainable Cities and Society, 48, 101580.
15. Clarke, L., Eoma, J., Marten, H. E., Horowitz, R., Kyle, P., Link, R., Mignone, B.K., Mundra, A and Zhoua, Y., 2019. Effects of long-term climate change on global building energy expenditures. Energy Economics, 72, pp.667-677.
16. Farah, S., Whaley, D., Saman, W and Boland, J., 2019. Integrating Climate Change into Meteorological Weather Data for Building Energy Simulation. Energy & Buildings, 183, pp.749-760.
17. Zhai, Z.J and Helman, M.J., 2019. Implications of Climate Changes to Building Energy and Design. Sustainable Cities and Society, 44, pp.511-519.
18. Yigit, S and Ozorhon, B., 2018. A Simulation-Based Optimization Method for Designing Energy Effcient Buildings: Energy & Buildings. 178, pp.216-227.
19. Kheiri, F., 2018. A review on optimization methods applied in energy-efficient building geometry and envelope design. Renewable and Sustainable Energy Reviews, 92, pp.892- 920.
20. Sembroiz, D., Careglio, D., Ricciardi, S and Fiore, U., 2018. Planning and operational energy optimization solutions for smart buildings. Information Sciences, 000, pp.1-14.
21. Zhao, D., Fana, H., Pana, L., Xua, Q and Zhangc, X., 2017. Energy Consumption Performance Considering Climate Change in Office Building. Procedia Engineering, 205, pp.3448- 3455.
22. Shi, X., Tian, Z., Chen, W.B and Jin, X., 2016. A review on building energy efficient design optimization rom the perspective of architects: Renewable and Sustainable Energy Reviews, 65, pp.872-884.
