Document Type : Research Article
Authors
Department of Building and Environment, School of Architecture and Environmental Design, University of Science and Technology, P. O. Box: 1684613114, Tehran, Iran.
Abstract
The height of buildings is one of the main features of urban configuration that affects energy consumption. However, to our knowledge, the complexity of relationships between the height parameters and energy use in urban blocks is poorly understood. In this context, the present study investigates the effect of the height distribution of buildings located in a residential complex on the energy consumption required for cooling and heating. This research simulates different possible layouts through computational software. For this purpose, first, the density of a residential complex was determined based on the rules and regulations of Tehran city and according to the site dimensions and certain site coverage. Then, the required building density was distributed in different layouts based on their diversity at different heights. The product of this stage involved 7 different layouts in which the height varied from 1 floor to the maximum number calculated in each part of the simulation. In the next step, the annual energy consumption for cooling and heating the complex was calculated for each of these layouts and compared with each other. The parametric generative model was created in the Grasshopper plugin from Rhino software, and the energy consumption was evaluated with the Honeybee plugin over one year. Also, the research findings were validated through DesignBuilder software using the EnergyPlus engine. The results of the energy simulation indicate that the height distribution of the blocks can have a significant effect on energy consumption. In the optimal case, proper layout reduces the annual cooling and heating energy consumption by 28 % and 13 %, respectively. Therefore, achieving an optimal value for each of the cooling and heating loads depends on the specific priorities and conditions of the design project. If the design project's priority is to reduce heating energy consumption, increasing the height and distributing the floors evenly between the blocks is a better answer. However, if the priority is to mitigate cooling energy consumption, the optimal layout can include low-rise blocks and a single very high-rise block.
Keywords
Main Subjects
- Asfour, O.S., & Alshawaf, E.S. (2015). Effect of housing density on energy efficiency of buildings located in hot climates. Energy and Buildings, 91, 131-138. https://doi.org/10.1016/j.enbuild.2015.01.030
- Chen, L., Hang, J., Sandberg, M., Claesson, L., Di Sabatino, S., & Wigo, H. (2017). The impacts of building height variations and building packing densities on flow adjustment and city breathability in idealized urban models. Building and Environment, 118, 344-361. https://doi.org/10.1016/j.buildenv.2017.03.042
- Chen, Y., Wu, J., Yu, K., & Wang, D. (2020). Evaluating the impact of the building density and height on the block surface temperature. Building and Environment, 168, 106493. https://doi.org/10.1016/j.buildenv.2019.106493
- Deng, J.-Y., Wong, N. H., & Zheng, X. (2016). The study of the effects of building arrangement on microclimate and energy demand of CBD in Nanjing, China. Procedia Engineering, 169, 44-54. https://doi.org/10.1016/j.proeng.2016.10.006
- Konis, K., Gamas, A., & Kensek, K. (2016). Passive performance and building form: An optimization framework for early-stage design support. Solar Energy, 125, 161-179. https://doi.org/10.1016/j.solener.2015.12.020
- Leng, H., Chen, X., Ma, Y., Wong, N.H., & Ming, T. (2020). Urban morphology and building heating energy consumption: Evidence from Harbin, a severe cold region city. Energy and Buildings, 224, 110143. https://doi.org/10.1016/j.enbuild.2020.110143
- Li, C., Song, Y., & Kaza, N. (2018). Urban form and household electricity consumption: A multilevel study. Energy and Buildings, 158, 181-193. https://doi.org/10.1016/j.enbuild.2017.10.007
- Li, Z., Chen, H., Lin, B., & Zhu, Y. (2018). Fast bidirectional building performance optimization at the early design stage. Building Simulation, 11(4), 647-661. https://www.researchgate.net/publication/322873680_Fast_bidirectional_building_performance_optimization_at_the_early_design_stage
- Martin, L., & March, L. (1972). Urban Space and Structures. Cambridge University Press. London.
- Mirashk-Daghiyan, M., Dehghan-Touran-Poshti, A., Shahcheragi, A., & Kaboli, M.H. (2022). The effect of surrounding buildings’ height and the width of the street on a building’s energy consumption. International Journal of Energy and Environmental Engineering, 13(1), 207-217. https://doi.org/10.1007/s40095-021-00420-1
- Mohajeri, N., Upadhyay, G., Gudmundsson, A., Assouline, D., Kämpf, J., & Scartezzini, J.-L. (2016). Effects of urban compactness on solar energy potential. Renewable Energy, 93, 469-482. https://doi.org/10.1016/j.renene.2016.02.053
- Poponi, D., Bryant, T., Burnard, K., Cazzola, P., Dulac, J., Fernandez Pales, A., Husar, J., Janoska, P., Masanet, E. R., Munuera, L., Remme, U., Teter, J., & West, K. (2016). Energy Technology Perspectives 2016: Towards Sustainable Urban Energy Systems. International Energy Agency. https://iea.blob.core.windows.net/assets/37fe1db9-5943-4288-82bf-13a0a0d74568/Energy_Technology_Perspectives_2016.pdf
- Quan, S.J. (2017). Energy efficient neighborhood design under residential zoning regulations in Shanghai. Energy Procedia, 143, 865-872. https://doi.org/10.1016/j.egypro.2017.12.775
- Quan, S.J., Li, Q., Augenbroe, G., Brown, J., & Yang, P.P.J. (2015). Urban data and building energy modeling: A GIS-based urban building energy modeling system using the urban-EPC engine. In S. Geertman, J. Jr. Ferreira, R. Goodspeed, & J. Stillwell (Eds.), Planning Support Systems and Smart Cities (pp. 447-469). Springer International Publishing. https://doi.org/10.1007/978-3-319-18368-8_24
- Resch, E., Bohne, R. A., Kvamsdal, T., & Lohne, J. (2016). Impact of urban density and building height on energy use in cities. Energy Procedia, 96, 800-814. https://doi.org/10.1016/j.egypro.2016.09.142
- Rode, P., Keim, C., Robazza, G., Viejo, P., & Schofield, J. (2014). Cities and energy: Urban morphology and residential heat-energy demand. Environment and Planning B: Planning and Design, 41(1), 138-162. https://doi.org/10.1068/b39065
- Roudsari, M., Pak, M., & Smith, A. (2013). Ladybug: A parametric environmental plugin for grasshopper to help designers create an environmentally-conscious design. Proceedings of the 13th Conference of the International Building Performance Simulation Association (pp. 3128-3135). France. https://www.researchgate.net/publication/287778694_Ladybug_A_parametric_environmental_plugin_for_grasshopper_to_help_designers_create_an_environmentally-conscious_design#fullTextFileContent
- Saebi Safa, B., Heidari, F., & Soleimanpour, N. (2020). Audit of energy loss through exterior walls of buildings and impact of thermal insulation with simulation in design builder software (Case study: Office building in Tehran). Journal of Science and Engineering Elites, 5(3), 169-179. (In Farsi). https://www.magiran.com/paper/2166038?lang=en
- Salvati, A., Coch, H., & Morganti, M. (2017). Effects of urban compactness on the building energy performance in Mediterranean climate. Energy Procedia, 122, 499-504. https://doi.org/10.1016/j.egypro.2017.07.303
- Salvati, A., Monti, P., Coch Roura, H., & Cecere, C. (2019). Climatic performance of urban textures: Analysis tools for a Mediterranean urban context. Energy and Buildings, 185, 162-179. https://doi.org/10.1016/j.enbuild.2018.12.024
- Sekhar Roy, S., Roy, R., & Balas, V. E. (2018). Estimating heating load in buildings using multivariate adaptive regression splines, extreme learning machine, a hybrid model of MARS and ELM. Renewable and Sustainable Energy Reviews, 82, 4256-4268. https://doi.org/10.1016/j.rser.2017.05.249
- Seyedzadeh, S., Rahimian, F., Glesk, I., & Roper, M. (2018). Machine learning for estimation of building energy consumption and performance: A review. Visualization in Engineering, 6(5), 1-20. https://doi.org/10.1186/s40327-018-0064-7
- Shareef, S., & Altan, H. (2022). Urban block configuration and the impact on energy consumption: A case study of sinuous morphology. Renewable and Sustainable Energy Reviews, 163, 112507. https://doi.org/10.1016/j.rser.2022.112507
- Shareef, S. (2021). The impact of urban morphology and building’s height diversity on energy consumption at urban scale. The case study of Dubai. Building and Environment, 194, 107675. https://doi.org/10.1016/j.buildenv.2021.107675
- Steemers, K. (2003). Cities, energy and comfort: A PLEA 2000 review. Energy and Buildings, 35(1), 1-2. https://doi.org/10.1016/S0378-7788(02)00074-9
- Terjung, W.H., & Louie, S.S.F. (1973). Solar radiation and urban heat islands. Annals of the Association of American Geographers, 63(2), 181-207. https://doi.org/10.1111/j.1467-8306.1973.tb00918.x
- Toutou, A., Fikry, M., & Mohamed, W. (2018). The parametric based optimization framework daylighting and energy performance in residential buildings in hot arid zone. Alexandria Engineering Journal, 57(4), 3595-3608. https://doi.org/10.1016/j.aej.2018.04.006
- Trepci, E., Maghelal, P., & Azar, E. (2020). Effect of densification and compactness on urban building energy consumption: Case of a transit-oriented development in Dallas, TX. Sustainable Cities and Society, 56, 101987. https://doi.org/10.1016/j.scs.2019.101987
- Vartholomaios, A. (2017). A parametric sensitivity analysis of the influence of urban form on domestic energy consumption for heating and cooling in a Mediterranean city. Sustainable Cities and Society, 28, 135-145. https://doi.org/10.1016/j.scs.2016.09.006
- Wong, N.H., Jusuf, S.K., Syafii, N.I., Chen, Y., Hajadi, N., Sathyanarayanan, H., & Manickavasagam, Y.V. (2011). Evaluation of the impact of the surrounding urban morphology on building energy consumption. Solar Energy, 85(1), 57-71. https://doi.org/10.1016/j.solener.2010.11.002
- Xu, X., AzariJafari, H., Gregory, J., Norford, L., & Kirchain, R. (2020). An integrated model for quantifying the impacts of pavement albedo and urban morphology on building energy demand. Energy and Buildings, 211, 109759. https://doi.org/10.1016/j.enbuild.2020.109759
- Yang, X., & Li, Y. (2015). The impact of building density and building height heterogeneity on average urban albedo and street surface temperature. Building and Environment, 90, 146-156. https://doi.org/10.1016/j.buildenv.2015.03.037
- Zhang, J., Liu, N., & Wang, S. (2020). A parametric approach for performance optimization of residential building design in Beijing. Building Simulation, 13(2), 223-235. https://link.springer.com/article/10.1007/s12273-019-0571-z
)