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

Abstract In the severe cold zones of China, solar radiation is one of the most important issues in architectural design. The design seeks to make buildings receive more direct sunlight within the limits of the user’s comfort and simultaneously save energy and space. So far in China, the design of solar radiation has usually been qualitative, not quantitative, and it is often implemented by architects with experience or those following convention. This rough and rigid design approach is not accurate or efficient, particularly in the design of free-form buildings, which comprise a class of irregular-form buildings popular in current architectural design. Moreover, solar radiation is not the only thing that needs to be considered; shape coefficient and space efficiency should also be considered in free-form building design. This study proposes a method for a free-form building that receives more solar radiation though shape optimization and takes into account the other two objectives mentioned above. This paper provides a method with a “Modeling–Simulation–Optimization” framework. In the process of applying this method, parametric modeling with Rhinoceros and Grasshopper is used to build up the free-form building model, and the shape optimization of the building is processed by using the multi-objective genetic algorithm to make sure the three objectives—i.e., to maximize solar radiation gain, to maximize space efficiency, and to minimize the shape coefficient—are all achieved. Finally, a Pareto frontier is generated to show the optimal solutions and to assist designers in making final decisions. The case study shows that compared with the cube-shaped reference building, the total solar radiation gain of the optimized free-form shape building is 30–53% higher, and the shape coefficient value is reduced by 15–20%, with a decrease of less than 5% of the space-efficiency values. The proposed method, according to the basic process of architecture design, uses a performance-driven approach to find solutions that satisfy the requirements. It can be used in real architectural design to solve practical optimization problems.

[1]  Moncef Krarti,et al.  Genetic-algorithm based approach to optimize building envelope design for residential buildings , 2010 .

[2]  I. Vizotto,et al.  Computational generation of free-form shells in architectural design and civil engineering , 2010 .

[3]  Gül Koçlar Oral,et al.  The limit U values for building envelope related to building form in temperate and cold climatic zones , 2002 .

[4]  Jérôme Henri Kämpf,et al.  Optimisation of building form for solar energy utilisation using constrained evolutionary algorithms , 2010 .

[5]  Gül Koçlar Oral,et al.  Building form for cold climatic zones related to building envelope from heating energy conservation point of view , 2003 .

[6]  Yun Kyu Yi,et al.  Agent-based geometry optimization with Genetic Algorithm (GA) for tall apartment’s solar right , 2015 .

[7]  Jae-Weon Jeong,et al.  Optimization of a free-form building shape to minimize external thermal load using genetic algorithm , 2014 .

[8]  R. G. Hopkinson,et al.  Sunlight requirements in buildings—I. Social survey , 1976 .

[9]  Darren Robinson,et al.  A hybrid CMA-ES and HDE optimisation algorithm with application to solar energy potential , 2009, Appl. Soft Comput..

[10]  Weimin Wang,et al.  Floor shape optimization for green building design , 2006, Adv. Eng. Informatics.

[11]  J. Virgone,et al.  Design of buildings shape and energetic consumption , 2001 .

[12]  Moncef Krarti,et al.  Building shape optimization using neural network and genetic algorithm approach , 2006 .

[13]  J. Kämpf,et al.  Optimisation of buildings' solar irradiation availability , 2010 .

[14]  Jae-Weon Jeong,et al.  Thermal characteristic prediction models for a free-form building in various climate zones , 2013 .

[15]  E. Ne'Eman.  Sunlight requirements in buildings—II. Visits of an assessment team and experiments in a controlled room , 1977 .

[16]  John S. Gero,et al.  Energy in context: A multicriteria model for building design , 1983 .

[17]  Weimin Wang,et al.  An object-oriented framework for simulation-based green building design optimization with genetic algorithms , 2005, Adv. Eng. Informatics.