Author
Listed:
- Jian Ma
(College of Civil Engineering and Architecture, Henan University of Technology, Zhengzhou 450001, China)
- Zhenxiang Cao
(College of Civil Engineering and Architecture, Henan University of Technology, Zhengzhou 450001, China)
- Jie Jian
(College of Civil Engineering and Architecture, Henan University of Technology, Zhengzhou 450001, China)
- Kunming Li
(College of Civil Engineering and Architecture, Henan University of Technology, Zhengzhou 450001, China)
- Jinyue Wu
(College of Civil Engineering and Architecture, Henan University of Technology, Zhengzhou 450001, China)
Abstract
During the adaptive reuse of industrial heritage buildings, existing opening systems and envelope performance often pose major constraints. These restrictions make it difficult for the building to meet the requirements of the updated indoor environment, resulting in insufficient daylight and increased energy consumption. Therefore, optimizing lighting and energy performance has become the primary goal of the retrofit design. However, with limited interventions, the retrofit of heritage buildings to achieve significant overall performance improvement is still a challenge. From a sustainability perspective, improving daylight utilization and reducing energy demand are essential strategies for achieving low-carbon and resource-efficient building retrofit. This study proposes a grid-based parametric multi-objective optimization approach to optimize the window openings of the building envelope. The approach defines the position, size and material properties of the roof and facade openings as design variables. Implemented via the Honeybee and Octopus platforms, it integrates a genetic algorithm with EnergyPlus and Radiance simulations to co-optimize daylight performance, circadian frequency, and energy use intensity. Taking a single-story typical industrial heritage building in China’s cold climate zone as a case study, it is shown that coordinated multi-objective constraints significantly improve the overall performance across various evaluation metrics. The optimization results also provide interpretable window configuration strategies and recommended parameter ranges, which fully consider the climate adaptability of the surrounding environment. These findings offer useful guidance for sustainable retrofit design decision-making in similar single-story industrial heritage buildings.
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