Explaining the Optimal Architectural Patterns of Residential Buildings from the Point of View of Energy (Case study of Tehran 12th District)

Subject Areas : Renewable Energy

Zohreh  Abbaszadeh ¹ (PhD Researcher in Architecture, Department of Architecture, Jolfa International Branch, Islamic Azad University, Jolfa, Iran.)
Masoud  Haghlesan ² (Assistant Professor, Department of Architecture and Urban Planning, Ilkhchi Branch, Islamic Azad University, Ilkhchi, Iran. *(Correspending Author))
Hassan  Ebrahimy Asl ³ (Assistant Professor, Department of Architecture, Jolfa International Branch, Islamic Azad University, Jolfa, Iran.)

Received: 2022-03-08 Accepted : 2022-12-20 Published : 2024-03-20

Keywords: Building, Energy, Optimal Consumption, Architecture, Zone 12 Tehran.,

Abstract :

Background and Objective: Due to the increasing price of energy carriers, energy consumption has become one of the main challenges. Meanwhile, residential buildings have a significant share in energy consumption. In Iran, the construction sector accounts for about 40% of total energy consumption and is one of the most consumed sectors of energy demand in the residential sector. Therefore, the purpose of this study is to explain the optimal architectural patterns of residential buildings from the point of view of energy. Material and Methodology: The method of this research is descriptive-analytical and survey. By examining the design examples of common buildings in District 12 of Tehran and modeling them with the help of "Design Builder" software, the amount of energy required for heating and cooling of the building and the effect of various factors on the energy consumption of the building were calculated. Findings: The results indicate that simple methods of interior and exterior architectural design of residential buildings can reduce energy consumption in the study areas by about 40% and also by developing architectural criteria for different areas of the city. Tehran and the application of these criteria in their design can be achieved a significant reduction in energy consumption of buildings and energy efficiency. Discussion and Conclusion: As a result of reducing the energy consumption of buildings with architectural design, this method of energy efficiency in buildings is highly compatible with the economic, cultural and social conditions of the residents of these areas. Have high success.

References:

1. Anastasiadou, M., Santos, V., & Dias, M. S. (2021). Machine Learning Techniques Focusing on the Energy Performance of Buildings: A Dimensions and Methods Analysis. Buildings, 12(1), 28.
2. Grillone, B., Danov, S., Sumper, A., Cipriano, J., & Mor, G. (2020). A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings. Renewable and Sustainable Energy Reviews, 131, 110027.
3. Gangolells, M., Casals, M., Ferré-Bigorra, J., Forcada, N., Macarulla, M., Gaspar, K., & Tejedor, B. (2020). Office representatives for cost-optimal energy retrofitting analysis: A novel approach using cluster analysis of energy performance certificate databases. Energy and Buildings, 206, 109557.
4. Cerquitelli, T., Di Corso, E., Proto, S., Bethaz, P., Mazzarelli, D., Capozzoli, A., ... & Tamburini, M. (2020). A Data-Driven Energy Platform: From Energy Performance Certificates to Human-Readable Knowledge through Dynamic High-Resolution Geospatial Maps. Electronics, 9(12), 2132.
5. Salata, F., Ciancio, V., Dell'Olmo, J., Golasi, I., Palusci, O., & Coppi, M. (2020). Effects of local conditions on the multi-variable and multi-objective energy optimization of residential buildings using genetic algorithms. Applied energy, 260, 114289.
6. Fan, Y., & Xia, X. (2018). Building retrofit optimization models using notch test data considering energy performance certificate compliance. Applied Energy, 228, 2140-2152.
7. Amiri Ade P, Tizghalam zenozi S, Javidi Nejad M. (2022). The effect of micro climate factors on energy consumption optimization approach in Tehran urban buildings. JGS; 22 (65) :265-282. (In Persian)
8. Asghari Alireza, Maliki Gavagani, Aida, Ebrahimi Asl Hassan, Sattari Sarbangoli, Hassan. (2020). Investigating the role of passive solar systems in zero energy urban buildings, for comfort and reducing energy consumption (Case study: Waliasr Shahratberiz), New perspectives in human geography, 2: 752-771. (In Persian)
9. Karimpour Alireza, Diba Darab, Itsam Iraj. (2017). Analyzing the effect of internal sunshades on energy consumption using simulation models (case study: residential unit in Tehran). City identity, 11(30), 17-30. (In Persian)
10. Anastasiadou, M., Santos, V., & Dias, M. S. (2021). Machine Learning Techniques Focusing on the Energy Performance of Buildings: A Dimensions and Methods Analysis. Buildings, 12(1), 28.
11. Klemm, C., & Wiese, F. (2022). Indicators for the optimization of sustainable urban energy systems based on energy system modeling. Energy, Sustainability and Society, 12(1), 1-20.
12. Haneef, F., Pernigotto, G., Gasparella, A., & Kämpf, J. H. (2021). Application of Urban Scale Energy Modelling and Multi-Objective Optimization Techniques for Building Energy Renovation at District Scale. Sustainability, 13(20), 11554.
13. Fathi, S., Srinivasan, R., Fenner, A., & Fathi, S. (2020). Machine learning applications in urban building energy performance forecasting: A systematic review. Renewable and Sustainable Energy Reviews, 133, 110287.
14. Mehmood, M. U., Chun, D., Han, H., Jeon, G., & Chen, K. (2019). A review of the applications of artificial intelligence and big data to buildings for energy-efficiency and a comfortable indoor living environment. Energy and Buildings, 202, 109383.
15. Abouzari Panthea, Ziyari Yusufali. Explaining the effects of improvement and renovation policies of dilapidated urban tissues (case study: District 12 of Tehran Municipality). New attitudes in human geography (human geography). 2018, 11(4): 491-510. (In Persian)
16. Farrokhzadeh Behnoosh, Kayani Arman, Bazarafshan Umm Albinin. Evaluation of SWMM hydrologic-hydraulic model in urban runoff management (case study: District 12 of Tehran Municipality). Economy and urban planning. 2019, 9(4), 243-251. (In Persian)