Tri-optimization of building shape and envelope properties using Taguchi and constraint limit method

PurposeThe purpose of this paper is to present a tri-optimization approach to optimize design solutions regarding the building shape and envelope properties considering their implications on thermal comfort, visual comfort and building energy consumption (EN). The optimization approach has been applied to obtain the optimal design solutions in five typical cities across all climatic regions of China.Design/methodology/approachThe method comprises a tri-optimization process with nine main steps to optimize the three objectives (thermal comfort, visual comfort and building EN). The design variables considered are four types of building shape (pyramid, rectangular, cylindrical and dome shape) and different envelope properties (insulation thickness [INS] of external walls/roof, window type [WT] and window-to-envelop surface area ratio [WESR]). The optimization is performed by using the Taguchi and constraint limit method.FindingsThe results show that the optimal design solutions for all climatic regions favor cylindrical shape and triple-layer low-E glazing window. The highest insulation level of 150 mm is preferred in three climatic regions, and the INS of 90 mm is preferred in the other two climate regions. In total, 10% WESR is preferred in all climatic regions, except the mild region. When the constraint limit of lighting intensity requirement by Leadership in Energy and Environmental Design (LEED) is applied, the rectangular shape building is the optimal solution for those with 10% WESR.Research limitations/implicationsThe method proposed in the paper is innovative in that it optimizes three different objectives simultaneously in building design with better accuracy and calculation speed.Practical implicationsBuilding designers can easily follow the proposed design guide in their practice which effectively bridges the gap between theory and practice. The optimal design solutions can provide a more comfortable living environment and yet less EN, which can help achieve the sustainability requirement of green buildings.Social implicationsThe solutions presented in the paper can serve as a useful guide for practical building designers which creates economic and commercial impact. In addition, the theory and practical examples of the study can be used by building regulators to improve the energy-efficient building design standard in China.Originality/valueThe research is the first attempt that adopts tri-optimization approach to generate the optimal solutions for building shape and envelope design. The tri-optimization approach can be used by building designers to generate satisfactory design solutions from the architectural viewpoint and meanwhile to find combinations of the building shape and envelope properties that lead to design solutions with optimal building performance.

[1]  Lingling Zhang,et al.  Shape optimization of free-form buildings based on solar radiation gain and space efficiency using a multi-objective genetic algorithm in the severe cold zones of China , 2016 .

[2]  Jing Zhao,et al.  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 , 2020, Solar Energy.

[3]  Sheryl Staub-French,et al.  Assessment of the Impact of Window Size, Position and Orientation on Building Energy Load Using BIM , 2016 .

[4]  Jérôme Henri Kämpf,et al.  Building shape optimisation to reduce air-conditioning needs using constrained evolutionary algorithms , 2015 .

[5]  Fan Zhang,et al.  Application of Taguchi method in optimising thermal comfort and cognitive performance during direct load control events , 2017 .

[6]  Vítor Leal,et al.  Building envelope shape design in early stages of the design process: Integrating architectural design systems and energy simulation , 2013 .

[7]  Vijay Kumar,et al.  A review on genetic algorithm: past, present, and future , 2020, Multimedia tools and applications.

[8]  Robert H. Lochner,et al.  PROS AND CONS OF TAGUCHI , 1991 .

[9]  Liu Xiaodong,et al.  Harvesting wind energy in low-rise residential buildings: Design and optimization of building forms , 2017 .

[10]  M. Susan Ubbelohde,et al.  THE ROLE OF DAYLIGHTING IN LEEDTM CERTIFICATION : A COMPARATIVE EVALUATION OF DOCUMENTATION METHODS , 2005 .

[11]  Patricia Edith Camporeale,et al.  Multi-objective optimisation model: A housing block retrofit in Seville , 2017 .

[12]  W. Harun,et al.  The Effects of Orientation, Ventilation, and Varied WWR on the Thermal Performance of Residential Rooms in the Tropics , 2011 .

[13]  Gabriele Lobaccaro,et al.  Parametric design to minimize the embodied GHG emissions in a ZEB , 2018 .

[14]  Shaoping Xu,et al.  Robust capacity optimization methods for integrated energy systems considering demand response and thermal comfort , 2021 .

[15]  A. Yigit,et al.  Experimental investigation of radiation effect on human thermal comfort by Taguchi method , 2016 .

[16]  Shiquan Zhou,et al.  Development of Building Thermal Load and Discomfort Degree Hour Prediction Models Using Data Mining Approaches , 2018 .

[17]  F. Calvino,et al.  Comparing different control strategies for indoor thermal comfort aimed at the evaluation of the energy cost of quality of building , 2010 .

[18]  Francisco Toja-Silva,et al.  An empirical–heuristic optimization of the building-roof geometry for urban wind energy exploitation on high-rise buildings , 2016 .

[19]  C. Yuan,et al.  Parametric study of ice thermal storage system with thin layer ring by Taguchi method , 2016 .

[20]  Hywel Rhys Thomas,et al.  Optimization of operating parameters of ground source heat pump system for space heating and cooling by Taguchi method and utility concept , 2014 .

[21]  Ra Rizki Mangkuto,et al.  Design optimisation for window size, orientation, and wall reflectance with regard to various daylight metrics and lighting energy demand: A case study of buildings in the tropics , 2016 .

[22]  Mustafa Inalli,et al.  Impacts of some building passive design parameters on heating demand for a cold region , 2006 .

[23]  Daisuke Sumiyoshi,et al.  Optimization of passive design measures for residential buildings in different Chinese areas , 2012 .

[24]  Debao Zhang,et al.  Research on the configuration and operation effect of the hybrid solar-wind-battery power generation system based on NSGA-II , 2019 .

[25]  Saeed Maghsoodloo,et al.  Strengths and limitations of taguchi's contributions to quality, manufacturing, and process engineering , 2004 .

[26]  Yaolin Lin,et al.  Optimization of a New Phase Change Material Integrated Photovoltaic/Thermal Panel with The Active Cooling Technique Using Taguchi Method , 2019, Energies.

[27]  Enedir Ghisi,et al.  Residential building design optimisation using sensitivity analysis and genetic algorithm , 2016 .

[28]  H. Jędrzejuk,et al.  Optimization of shape and functional structure of buildings as well as heat source utilisation example , 2002 .

[29]  Wei Yang,et al.  A Study on the Impact of Household Occupants’ Behavior on Energy Consumption Using an Integrated Computer Model , 2015, Front. Built Environ..

[30]  Wojciech Marks,et al.  MULTICRITERIA OPTIMISATION OF SHAPE OF ENERGY-SAVING BUILDINGS , 1997 .

[31]  Mohammadjavad Mahdavinejad,et al.  Optimisation of building shape and orientation for better energy efficient architecture , 2015 .

[32]  Farshad Kowsary,et al.  Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO) , 2016 .

[33]  Miroslav Premrov,et al.  Influence of the building shape on the energy performance of timber-glass buildings located in warm climatic regions , 2018 .

[34]  Rabee M. Reffat,et al.  Generating proper building envelopes for photovoltaics integration with shape grammar theory , 2018 .

[35]  Sanaz Tabatabaee,et al.  Assessment of the building components in the energy efficient design of tropical residential buildings: An application of BIM and statistical Taguchi method , 2019 .

[36]  Jiangjiang Wang,et al.  Review on multi-criteria decision analysis aid in sustainable energy decision-making , 2009 .