Multi-Objective Optimization Method for the Shape of Large-Space Buildings Dominated by Solar Energy Gain in the Early Design Stage

Abstract

Large-space buildings feature a sizable interface for receiving solar radiation, and optimizing their shape in the early design stage can effectively increase their solar energy harvest while considering both energy efficiency and space utilization. A large-space building shape optimization method was developed based on the “modeling-calculation-optimization” process to transform the “black box” mode in traditional design into a “white box” mode. First, a two-level node control system containing core space variables and envelope variables is employed to construct a parametric model of the shape of a large-space building. Second, three key indicators, i.e., annual solar radiation, surface coefficient, and space efficiency, are used to representatively quantify the performance in terms of sunlight capture, energy efficiency, and space utilization. Finally, a multi-objective genetic algorithm is applied to iteratively optimize the building shape, and the Pareto Frontier formed by the optimization results provides the designer with sufficient alternatives and can be used to assess the performance of different shapes. Further comparative analysis of the optimization results can reveal the typical shape characteristics of the optimized solutions and potentially determine the key variables affecting building performance. In a case study of six large-space buildings with typical shapes, the solar radiation of the optimized building shape solutions was 13.58–39.74% higher than that of reference buildings 1 and 3; compared with reference buildings 2 and 4, the optimized solutions also achieved an optimal balance of the three key indicators. The results show that the optimization method can effectively improve the comprehensive performance of buildings.