Comparison analysis on simplification methods of building performance optimization for passive building design

Abstract

Building performance optimization (BPO) is effective for designers to explore passive building alternatives based on defined performance metrics. As the first step of BPO, the simplification of design problems has been performed in diverse methods. However, its identification and selection are still a challenge. This study firstly develops a simplification matrix based on two criteria of complexity and flexibility to categorize existing passive design options. Secondly, four simplified configurations are compared to evaluate their impact on the quality and correlation of optimized solutions. A prefabricated building was selected as the case study, and three performance metrics were defined as energy use intensity, thermal discomfort ratio and dissatisfaction of daylight illuminance. In the results, the low-complexity model with high flexibility outperforms the other simplifications with expected improvements of 20.16%, 15.14% and 47.09% for three metrics. However, the difference in improvements between low- and high-flexibility models lies within 2%. Based on the results, the low-complexity model with low flexibility would be the most promising simplified method, as it can integrate engineering information into BPO with a negligible performance gap. Moreover, it is also found that the correlation varies significantly between low- and high-complexity models, which is caused by the variation of the transparent parameter from window to glass. Finally, the multi-objective genetic algorithm II has an advantage in convergence speed over the non-dominated sorting genetic algorithm II.