Building performance optimization is a powerful technique that assists designers in identifying optimal design solutions. However, occupant-related uncertainty is considered a major challenge that can influence the credibility of the selected optimal design. This paper proposes an occupant-centric method for window and shading design optimization in office buildings that assists designers in evaluating and handling the impact of occupant-related assumptions. The method consists of three major steps: generating occupant scenarios, conducting occupant-centric mathematical optimization, and deriving rules for selecting optimal design parameters using decision trees. An office building model with numerous possible window-related parameters was used to demonstrate the proposed optimization process. Sixty-four different occupant scenarios were considered. The results of the optimization process demonstrated that occupant-related assumptions are crucial in determining optimal window and shading design, as different occupant scenarios led to different optimal solutions. The study findings also provided insights to building designers regarding classifying and selecting window and shading design parameters under varying occupant scenarios.

建筑性能优化是一项强大的技术，可帮助设计师确定最佳设计解决方案。但是，与乘员相关的不确定性被认为是一项重大挑战，可能会影响所选最优设计的可信度。本文提出了一种以居住者为中心的办公楼窗户和遮阳设计优化方法，该方法可帮助设计师评估和处理与居住者有关的假设的影响。该方法包括三个主要步骤：生成乘员情景，进行以乘员为中心的数学优化以及使用决策树推导选择最佳设计参数的规则。使用具有众多可能的与窗口相关的参数的办公楼模型来演示建议的优化过程。考虑了64种不同的乘员情景。优化过程的结果表明，与乘员相关的假设对于确定最佳的窗户和遮阳设计至关重要，因为不同的乘员场景导致了不同的最佳解决方案。研究结果还为建筑设计师提供了有关在变化的乘员情景下分类和选择窗户和遮阳设计参数的见解。