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Building performance is heavily influenced by weather conditions. Though the climate is changing vastly, few building performance optimizations (BPO) consider global warming over the life expectancy of the buildings. This paper develops a novel multi-objective BPO framework by the using simulation-based surrogate models under the future weather conditions that are determined by morphing the typical meteorological year (TMY) data. This framework is adopted to optimize a typical classroom in a hot and humid area under the future weather scenarios of representative concentration pathways (RCP) 4.5 and 8.5. The energy, thermal comfort and daylighting performances with and without considering the climate changes in the optimizations are compared and their notable differences are discussed. Under future climate, the optimization considering the future climate change improves the building performances significantly compared to the optimization without any climate change considerations (i.e., using the historical TMY). Especially, the winter discomfort hours in RCP4.5 and 8.5 decrease by 7.4% and 13.3%, respectively, when such future climate changes are considered in the BPOs, compared to the BPOs using the historical TMY data. The results show that BPO without considering climate change effects may cause non-negligible uncertainties. The proposed method can effectively improve the building performance in a changing climate.
Zou et al. (Sat,) studied this question.