A Framework for Adaptive Façade Optimization Design Based on Building Envelope Performance Characteristics

Author:

Chen Ping1ORCID,Tang Hao1

Affiliation:

1. School of Architecture and Urban Planning (SAU), Shandong Jianzhu University, Jinan 250101, China

Abstract

The adaptive façades serve as the interface between the indoor and outdoor energy of the building. Adaptive façade optimization design can improve daylighting performance, the thermal environment, view performance, and solar energy utilization efficiency, thus reducing building energy consumption. However, traditional design frameworks often neglect the influence of building envelope performance characteristics on adaptive façade optimization design. This paper aims to reveal the potential functional relationship between building façade performance characteristics and adaptive façade design. It proposes an adaptive façade optimization design framework based on building envelope performance characteristics. The method was then applied to a typical office building in northern China. This framework utilizes a K-means clustering algorithm to analyze building envelope performance characteristics, establish a link to adaptive façade design, and use the optimization algorithm and machine learning to make multi-objective optimization predictions. Finally, Pearson’s correlation analysis and visual decision tools were employed to explore the optimization potential of adaptive façades concerning indoor daylighting performance, view performance, and solar energy utilization. The results showed that the optimized adaptive façade design enhances useful daylight illuminance (UDI) by 0.52%, quality of view (QV) by 5.36%, and beneficial solar radiation energy (BSR) by 14.93% compared to traditional blinds. In addition, each office unit can generate 309.94 KWh of photovoltaic power per year using photovoltaic shading systems. The framework provides new perspectives and methods for adaptive façade optimization design, which helps to achieve multiple performance objectives for buildings.

Funder

Natural Science Foundation of Shandong Province

Publisher

MDPI AG

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