Abstract
The window and shading configuration is the weak link of heat insulation in the outer protective structure. And it is also an important means of visual performance, which plays an important part in building energy savings. Resulting from the influence of weather and solar radiation, there are contradictions among the energy consumption, visual performance and thermal environment. Therefore, in order to optimize the three factors, an effective optimization method is necessary. For the window design, the existing studies mostly focus on the analysis of energy consumption performance, less on the sound insulation performance. In addition, the optimal configuration of windows and shading system under different climatic regions and orientations has been solved. In this paper, a multi-objective optimization model considering building energy consumption, thermal environment and visual performance was proposed by introducing window orientation, window–wall ratio, window configuration, shading angle and length parameters. And it uses the non-dominated sequencing genetic algorithm NSGA-II and energy simulation software EnergyPlus. The corresponding Pareto solution set was obtained from the assumed room in a cold region, hot summer and cold winter region and hot summer and warm winter region, respectively. The optimal recommended values of window parameters in each direction were determined by analyzing the Pareto solution set. The effectiveness of the multi-objective optimization model is proved by using the linear weighted sum method, and the optimization method of sound insulation effect is discussed. The optimization model in this paper is helpful for designers to choose the optimal design scheme, so that it can comply with the design requirements in terms of energy consumption, thermal environment, visual performance and achieve the overall optimal performance.
Similar content being viewed by others
References
IEA—International Energy Agency: IEA—International Energy Agency. https://www.iea.org. Accessed 29 May 2020
The 13th five-year plan for economic and social development of the People Republic of China. http://www.gov.cn/xinwen/2016-03/17/content_5054992.htm (2016). Accessed 29 May 2020
Echenagucia, T.M., Capozzoli, A., Cascone, Y., Sassone, M.: The early design stage of a building envelope: multi-objective search through heating, cooling and lighting energy performance analysis. Appl Energy 154, 577–591 (2015). https://doi.org/10.1016/j.apenergy.2015.04.090
Mangkuto, R.A., Dewi, D.K., Herwandani, A.A., Koerniawan, M.D.: Faridah: design optimisation of internal shading device in multiple scenarios: case study in Bandung, Indonesia. J. Build. Eng. 24, 100745 (2019). https://doi.org/10.1016/j.jobe.2019.100745
Aydn, D., Mihlayanlar, E.: A case study on the impact of building envelope on energy efficiency in high-rise residential building. Arch. Civ. Eng. Environ. 13(1), 5–18 (2020). https://doi.org/10.21307/ACEE-2020-001
Zhai, Y., Wang, Y., Huang, Y., Meng, X.: A multi-objective optimization methodology for window design considering energy consumption, thermal environment and visual performance. Renew Energy 134, 1190–1199 (2019). https://doi.org/10.1016/j.renene.2018.09.024
Sun, Y., Wilson, R., Wu, Y.: A review of transparent insulation material (TIM) for building energy saving and daylight comfort. Appl Energy 226, 713–729 (2018). https://doi.org/10.1016/j.apenergy.2018.05.094
Xiaotu, L.: Architectural Physics. China Architecture & Building Press, Beijing (2010)
Manzan, M.: Genetic optimization of external fixed shading devices. Energy Build. 72, 431–440 (2014). https://doi.org/10.1016/j.enbuild.2014.01.007
Lau, A.K.K., Salleh, E., Lim, C.H., Sulaiman, M.Y.: Potential of shading devices and glazing configurations on cooling energy savings for high-rise office buildings in hot-humid climates: the case of Malaysia. Int. J. Sustain. Built Environ. 5(2), 387–399 (2016). https://doi.org/10.1016/j.ijsbe.2016.04.004
Al-Masrani, S.M., Al-Obaidi, K.M., Zalin, N.A., Aida Isma, M.I.: Design optimisation of solar shading systems for tropical office buildings: challenges and future trends. Sol. Energy 170, 849–872 (2018). https://doi.org/10.1016/j.solener.2018.04.047
Goia, F., Haase, M., Perino, M.: Optimizing the configuration of a façade module for office buildings by means of integrated thermal and lighting simulations in a total energy perspective. Appl Energy 108, 515–527 (2013). https://doi.org/10.1016/j.apenergy.2013.02.063
Alam, M.J., Islam, M.A.: Effect of external shading and window glazing on energy consumption of buildings in Bangladesh. Adv. Build. Energy Res. 11(2), 180–192 (2017). https://doi.org/10.1080/17512549.2016.1190788
Khoroshiltseva, M., Slanzi, D., Poli, I.: A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices. Appl. Energy 184, 1400–1410 (2016). https://doi.org/10.1016/j.apenergy.2016.05.015
Carlucci, S., Cattarin, G., Causone, F., Pagliano, L.: 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 Build. 104, 378–394 (2015). https://doi.org/10.1016/j.enbuild.2015.06.064
Shi, X., Tian, Z., Chen, W., Si, B., Jin, X.: A review on building energy efficient design optimization rom the perspective of architects. Renew. Sustain. Energy Rev. 65, 872–884 (2016). https://doi.org/10.1016/j.rser.2016.07.050
Susorova, I., Tabibzadeh, M., Rahman, A., Clack, H.L., Elnimeiri, M.: The effect of geometry factors on fenestration energy performance and energy savings in office buildings. Energy Build. 57, 6–13 (2013). https://doi.org/10.1016/j.enbuild.2012.10.035
Li, Z., Chen, H., Lin, B., Zhu, Y.: Fast bidirectional building performance optimization at the early design stage. Build. Simul. 004(011), 647–661 (2018)
Vallée, J., Ferrara, M., Astolfi, A., Fabrizio, E.: Trade-off between sound insulation performance and cost-optimality in a residential nZEB. Energy Procedia 140, 57–66 (2017). https://doi.org/10.1016/j.egypro.2017.11.123
Wu, W., Guo, J., Li, J., Hou, H., Meng, Q., Wang, W.: A multi-objective optimization design method in zero energy building study: a case study concerning small mass buildings in cold district of China. Energy Build. 158, 1613–1624 (2018). https://doi.org/10.1016/j.enbuild.2017.10.102
Wang, R., Lu, S., Feng, W.: A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost. Energy 192, 116723 (2020). https://doi.org/10.1016/j.energy.2019.116723
Bingham, R.D., Agelin-Chaab, M., Rosen, M.A.: Whole building optimization of a residential home with PV and battery storage in the Bahamas. Renew. Energy 132, 1088–1103 (2019). https://doi.org/10.1016/j.renene.2018.08.034
Ochoa, C.E., Aries, M.B.C., van Loenen, E.J., Hensen, J.L.M.: Considerations on design optimization criteria for windows providing low energy consumption and high visual comfort. Appl. Energy 95, 238–245 (2012). https://doi.org/10.1016/j.apenergy.2012.02.042
Harmathy, N., Magyar, Z., Folić, R.: Multi-criterion optimization of building envelope in the function of indoor illumination quality towards overall energy performance improvement. Energy 114, 302–317 (2016). https://doi.org/10.1016/j.energy.2016.07.162
Lee, J.W., Jung, H.J., Park, J.Y., Lee, J.B., Yoon, Y.: Optimization of building window system in Asian regions by analyzing solar heat gain and daylighting elements. Renew. Energy 50, 522–531 (2013). https://doi.org/10.1016/j.renene.2012.07.029
Kwon, H.J., Yeon, S.H., Lee, K.H., Lee, K.H.: Evaluation of building energy saving through the development of venetian blinds’ optimal control algorithm according to the orientation and window-to-wall ratio. Int. J. Thermophys. 39(2), 30 (2018). https://doi.org/10.1007/s10765-017-2350-3
Zhao, J., Du, Y.: Multi-objective optimization design for windows and shading configuration considering energy consumption and thermal comfort: a case study for office building in different climatic regions of China. Sol. Energy 206, 997–1017 (2020). https://doi.org/10.1016/j.solener.2020.05.090
Crawley, D., Hand, J.: Contrasting the capabilities of building energy performance simulation programs. Build. Environ. 43(4), 661–673 (2008). https://doi.org/10.1016/j.buildenv.2006.10.027
Goldstein, D.B., Eley, C.: A classification of building energy performance indices. Energy Effic. 7(2), 353–375 (2014). https://doi.org/10.1007/s12053-013-9248-0
OpenStudio: OpenStudio. https://www.openstudio.net/ (2020). Accessed 10 May 2020
Ascione, F., Bianco, N., Mauro, G.M., Napolitano, D.F.: Retrofit of villas on Mediterranean coastlines: Pareto optimization with a view to energy-efficiency and cost-effectiveness. Appl. Energy 254, 113705 (2019). https://doi.org/10.1016/j.apenergy.2019.113705
Nguyen, A., Reiter, S., Rigo, P.: A review on simulation-based optimization methods applied to building performance analysis. Appl. Energy 113, 1043–1058 (2014). https://doi.org/10.1016/j.apenergy.2013.08.061
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.A.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evolut. Comput. 6(2), 182–197 (2002). https://doi.org/10.1109/4235.996017
Harkouss, F., Fardoun, F., Biwole, P.H.: Multi-objective optimization methodology for net zero energy buildings. J. Build. Eng. 16, 57–71 (2018). https://doi.org/10.1016/j.jobe.2017.12.003
Delgarm, N., Sajadi, B., Delgarm, S., Kowsary, F.: A novel approach for the simulation-based optimization of the buildings energy consumption using NSGA-II: case study in Iran. Energy Build. 127, 552–560 (2016). https://doi.org/10.1016/j.enbuild.2016.05.052
Gong, X., Akashi, Y., Sumiyoshi, D.: Optimization of passive design measures for residential buildings in different Chinese areas. Build. Environ. 58, 46–57 (2012). https://doi.org/10.1016/j.buildenv.2012.06.014
Fang, Y., Cho, S.: Design optimization of building geometry and fenestration for daylighting and energy performance. Sol. Energy 191, 7–18 (2019). https://doi.org/10.1016/j.solener.2019.08.039
Reinhart, C.F., Mardaljevic, J., Rogers, Z.: Dynamic daylight performance metrics for sustainable building design. Leukos 3(1), 7–31 (2006). https://doi.org/10.1582/LEUKOS.2006.03.01.001
Carlucci, S., Causone, F., De Rosa, F., Pagliano, L.: A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design. Renew. Sustain. Energy Rev. 47, 1016–1033 (2015). https://doi.org/10.1016/j.rser.2015.03.062
Fanger, P.O., Melikov, A.K., Hanzawa, H., Ring, J.: Air turbulence and sensation of draught. Energy Build. 12(1), 21–39 (1988)
Yucheng, K.: Building Sound Insulation Design: Air Sound Insulation Technology. China Architecture & Building Press, Beijing (2004)
Protection, M.O.U.A.: Code for design of sound insulation of civil buildings GB50118-2010 (2011)
Administration, S.E.P.: Environment quality standard for noise GB3096-2008. (2008)
Srinivas, M., Patnaik, L.M.: Genetic algorithms: a survey. Computer 6(27), 17–26 (2002). https://doi.org/10.1109/2.294849
Lei, Y.S.Z.X.: MATLAB Genetic Algorithm Toolbox and Application. Xidian University Press, Xi’an (2005)
Ribeiro Filho, J.L., Treleaven, P.C.: Genetic-algorithm programming environments. Computer 27(6), 28–43 (1994). https://doi.org/10.1109/2.294850
Ascione, F., Bianco, N., De Stasio, C., Mauro, G.M., Vanoli, G.P.: Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: a new approach to assess cost-optimality. Appl Energy 174, 37–68 (2016). https://doi.org/10.1016/j.apenergy.2016.04.078
Delgarm, N., Sajadi, B., Kowsary, F., Delgarm, S.: Multi-objective optimization of the building energy performance: a simulation-based approach by means of particle swarm optimization (PSO). Appl Energy 170, 293–303 (2016). https://doi.org/10.1016/j.apenergy.2016.02.141
Bre, F., Silva, A.S., Ghisi, E., Fachinotti, V.D.: Residential building design optimisation using sensitivity analysis and genetic algorithm. Energy Build. 133, 853–866 (2016). https://doi.org/10.1016/j.enbuild.2016.10.025
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Sun, Z., Cao, Y., Wang, X. et al. Multi-objective optimization design for windows and shading configuration: considering energy consumption, thermal environment, visual performance and sound insulation effect. Int J Energy Environ Eng 12, 805–836 (2021). https://doi.org/10.1007/s40095-021-00413-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40095-021-00413-0