Document Type : Original Article


1 Department of Civil Engineering, Chalous Branch, Islamic Azad University, Chalous, Iran

2 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC, Canada


The purpose of this research is to analyze the energy of a residential building in the city of Tabriz with a cold and dry climate using energy simulation to provide a model to minimize energy consumption. A comparative model of energy consumption analysis in a three-story building unit with dimensions of 181 square meters is presented using 5 layout modes in the wall, floor, ceiling, window and door. The number of 5 designs with different arrangement of rooms and different number of windows were compared in terms of energy conservation in 51 different diagrams and the optimal energy saving design is selected. In the next step, according to the obtained results, the design of the building in the desired site is discussed. At the end, in order to check the amount of energy absorbed in the building, energy diagrams will be obtained for the thermal region of the coldest day of the year. The results show that the most optimal energy consumption of the residential building is related to the design of plan B with the fabric gains value of 41767 Wh. After that, the designed plan A show the most optimal energy consumption in the building with fabric gains value of 41028 Wh in the month of July. The results of this research are useful for energy ‎efficiency of residential buildings and environmental management in future.


Main Subjects

  1. Amani N, Reza Soroush AA, Moghadas Mashhad M, Safarzadeh K. Energy analysis for construction of a zero-energy residential building using thermal simulation in Iran. International Journal of Energy Sector Management. 2021;15(5):895–913. Doi: 10.1108/ijesm-05-2020-0018.
  2. Gandjalikhan Nassab SA, Moein Addini M. Effect of Radiative Filling Gas in Compound Parabolic Solar Energy Collectors. Iranian Journal of Energy and Environment. 2021;12(3):181–91. Doi: 10.5829/ijee.2021.12.03.01.
  3. Mohammadi A, Hakimizadeh M. Investigation of Volume Changes in Carbon Dioxide Hydrate Formation Process. Iranica Journal of Energy and Environment. 2024;15(2):135–41. Doi: 10.5829/ijee.2024.15.02.02.
  4. Gibbs D, O’Neill K. Rethinking sociotechnical transitions and green entrepreneurship: The potential for transformative change in the green building sector. Environment and Planning A. 2014;46(5):1088–107. Doi: 10.1068/a46259.
  5. Guironnet A, Attuyer K, Halbert L. Building cities on financial assets: The financialisation of property markets and its implications for city governments in the Paris city-region. Urban Studies. 2016;53(7):1442–64. Doi: 10.1177/0042098015576474.
  6. Aghagolzadeh Silakhor R, Jahanian O, Alizadeh Kharkeshi B. Investigating a Combined Cooling, Heating and Power System from Energy and Exergy Point of View with RK-215 ICE Engine as a Prime Mover. Iranian Journal of Energy and Environment. 2023;14(1):65–75. Doi: 10.5829/ijee.2023.14.01.09.
  7. Amani N, Soroush AAR. Effective energy consumption parameters in residential buildings using Building Information Modeling. Global Journal of Environmental Science and Management. 2020;6(4):467–80. Doi: 10.22034/gjesm.2020.04.04.
  8. Nguyen TT, Nguyen TT, Hoang VN, Wilson C, Managi S. Energy transition, poverty and inequality in Vietnam. Energy Policy. 2019;132:536–48. Doi: 10.1016/j.enpol.2019.06.001.
  9. Amani N. Energy Simulation and Management of the Main Building Component Materials Using Comparative Analysis in a Mild Climate Zone. Journal of Renewable Energy and Environment. 2020;7(3):29–46.
  10. Amani N. Building energy conservation in atrium spaces based on ECOTECT simulation software in hot summer and cold winter zone in Iran. International Journal of Energy Sector Management. 2018;12(3):298–313. Doi: 10.1108/ijesm-05-2016-0003/full/html.
  11. Amani N. Energy efficiency using the simulation software of atrium thermal environment in residential building: a case study. Advances in Building Energy Research. 2019;13(1):65–79. Doi: 10.1080/17512549.2017.1354781.
  12. Hamed RED. Harmonization between architectural identity and energy efficiency in residential sector (case of North-West coast of Egypt). Ain Shams Engineering Journal. 2018;9(4):2701–8. Doi: 10.1016/j.asej.2017.09.001.
  13. Krishnaraj L, Kumar VRP, Balasubramanian M, Kumar N, Shyamala T. Futuristic evaluation of building energy simulation model with comparison of conventional villas. International Journal of Construction Management. 2022;22(1):31–40. Doi: 10.1080/15623599.2019.1579968.
  14. Dabe TJ, Adane VS. The impact of building profiles on the performance of daylight and indoor temperatures in low-rise residential building for the hot and dry climatic zones. Building and Environment. 2018;140:173–83. Doi: 10.1016/j.buildenv.2018.05.038.
  15. Shayan ME, Najafi G, Ghobadian B, Gorjian S, Mamat R, Ghazali MF. Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm. Renewable Energy. 2022;201:179–89. Doi: 10.1016/j.renene.2022.11.006.
  16. Esmaeili Shayan M, Najafi G, Lorenzini G. Phase change material mixed with chloride salt graphite foam infiltration for latent heat storage applications at higher temperatures and pressures. International Journal of Energy and Environmental Engineering. 2022;13(2):739–49. Doi: 10.1007/s40095-021-00462-5.
  17. Shayan ME, Najafi G, Ghobadian B, Gorjian S, Mazlan M, Samami M, Shabanzadeh A. Flexible Photovoltaic System on Non-Conventional Surfaces: A Techno-Economic Analysis. Sustainability (Switzerland). 2022;14(6). Doi: 10.3390/su14063566.
  18. Esmaeili Shayan M, Esmaeili Shayan S, Nazari A. Possibility of supplying energy to border villages by solar energy sources. Energy Equipment and Systems. 2021;9(3):279–89. Doi: 10.22059/ees.2021.246079.
  19. Shayan ME, Najafi G, Ghobadian B, Gorjian S, Mazlan M. A novel approach of synchronization of the sustainable grid with an intelligent local hybrid renewable energy control. International Journal of Energy and Environmental Engineering. 2023;14(1):35–46. Doi: 10.1007/s40095-022-00503-7.
  20. Esmaeili Shayan M, Najafi G, Esmaeili Shayan S. Energy Management Model for a Standalone Hybrid Microgrid Using a Dynamic Decision-Making Algorithm. Amirkabir Journal of Mechanical Engineering. 2023;55(1):3–20. Doi: 10.22060/mej.2023.20755.7346.
  21. Mendes VF, Cruz AS, Gomes AP, Mendes JC. A systematic review of methods for evaluating the thermal performance of buildings through energy simulations. Renewable and Sustainable Energy Reviews. 2024;189. Doi: 10.1016/j.rser.2023.113875.
  22. Gennaro G, Catto Lucchino E, Goia F, Favoino F. Modelling double skin façades (DSFs) in whole-building energy simulation tools: Validation and inter-software comparison of naturally ventilated single-story DSFs. Building and Environment. 2023;231. Doi: 10.1016/j.buildenv.2023.110002.
  23. d’Ambrosio Alfano FR, Pepe D, Riccio G, Vio M, Palella BI. On the effects of the mean radiant temperature evaluation in the assessment of thermal comfort by dynamic energy simulation tools. Building and Environment. 2023;236. Doi: 10.1016/j.buildenv.2023.110254.
  24. Hasan S, Usmani J, Islam M. Simulation of Energy Conservation in a Building: A Case Study. Iranian (Iranica) Journal of Energy & Environment. 2018;9(1):10–5. Doi: 10.5829/ijee.2018.09.01.02.
  25. Tayari N, Nikpour M. Investigating DesignBuilder Simulation Software’s Validation in Term of Heat Gain through Field Measured Data of Adjacent Rooms of Courtyard House. Iranian Journal of Energy and Environment. 2023;14(1):1–8. Doi: 10.5829/ijee.2023.14.01.01.
  26. Xu F, Liu Q. Building energy consumption optimization method based on convolutional neural network and BIM. Alexandria Engineering Journal. 2023;77:407–17. Doi: 10.1016/j.aej.2023.06.084.
  27. Elsayed P, Mostafa H, Marzouk M. BIM based framework for building evacuation using Bluetooth Low Energy and crowd simulation. Journal of Building Engineering. 2023;70. Doi: 10.1016/j.jobe.2023.106409.
  28. Shen Y, Pan Y. BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization. Applied Energy. 2023;333. Doi: 10.1016/j.apenergy.2022.120575.
  29. Abdullah AH, Meng Q, Zhao L, Wang F. Field study on indoor thermal environment in an atrium in tropical climates. Building and Environment. 2009;44(2):431–6. Doi: 10.1016/j.buildenv.2008.02.011.
  30. Ham Y, Golparvar-Fard M. EPAR: Energy Performance Augmented Reality models for identification of building energy performance deviations between actual measurements and simulation results. Energy and Buildings. 2013;63:15–28. Doi: 10.1016/j.enbuild.2013.02.054.
  31. Climate & Temperature. 2021. ‎Available from:
  32. Iran of Meteorological Organization. 2020. ‎Available from:
  33. Climate Consultant 6.0. ‎Available from:
  34. Vangimalla PR, Olbina SJ, Issa RR, Hinze J. Validation of autodesk EcotectTM accuracy for thermal and daylighting simulations. Proceedings - Winter Simulation Conference. 2011;3383–94. Doi: 10.1109/wsc.2011.6148034.
  35. Abdullah AH, Bakar SKA, Rahman IA. Simulation of office’s operative temperature using Ecotect Model. International Journal of Construction Technology and Management. 2013;1(1):33–7.
  36. Amani N, Sabamehr A, Palmero Iglesias LM. Review on Energy Efficiency using the Ecotect Simulation Software for Residential Building Sector. Iranian Journal of Energy and Environment. 2022;13(3):284–94. Doi: 10.5829/ijee.2022.13.03.08.
  37. Wang E, Shen Z, Barryman C. A Building LCA Case Study Using Autodesk Ecotect and BIM Model. 47th ASC Annual International Conference Proceedings. 2011;
  38. Crawley DB, Hand JW, Kummert M, Griffith BT. Contrasting the capabilities of building energy performance simulation programs. Building and Environment. 2008;43(4):661–73. Doi: 10.1016/j.buildenv.2006.10.027.
  39. Wu Q, Jo HK. A study on Ecotect application of local climate at a residential area in Chuncheon, Korea. Journal of Environmental Engineering and Landscape Management. 2015;23(2):94–101. Doi: 10.3846/16486897.2014.980264.