The energy-efficient building design requires building performance simulation (BPS) to compare multiple design options for their energy performance. However, at the early stage, BPS is often ignored, due to uncertainty, lack of details, and computational time. This article studies probabilistic and deterministic approaches to treat uncertainty; detailed and simplified zoning for creating zones; and dynamic simulation and machine learning for making energy predictions. A state-of-the-art approach, such as dynamic simulation, provide a reliable estimate of energy demand, but computationally expensive. Reducing computational time requires the use of an alternative approach, such as a machine learning (ML) model. However, an alternative approach will cause a prediction gap, and its effect on comparing options needs to be investigated. A plugin for Building information modelling (BIM) modelling tool has been developed to perform BPS using various approaches. These approaches have been tested for an office building with five design options. A method using the probabilistic approach to treat uncertainty, detailed zoning to create zones, and EnergyPlus to predict energy is treated as the reference method. The deterministic or ML approach has a small prediction gap, and the comparison results are similar to the reference method. The simplified model approach has a large prediction gap and only makes only 40% comparison results are similar to the reference method. These findings are useful to develop a BIM integrated tool to compare options at the early design stage and ascertain which approach should be adopted in a time-constraint situation.

节能建筑设计需要建筑性能模拟（BPS），以比较多个设计方案的能源性能。但是，由于不确定性，缺乏细节和计算时间，在早期阶段，BPS通常被忽略。本文研究概率和确定性方法来处理不确定性。用于创建区域的详细和简化的分区；动态仿真和机器学习来进行能量预测。最新的方法（例如动态仿真）可提供可靠的能源需求估算，但计算量大。减少计算时间要求使用替代方法，例如机器学习（ML）模型。但是，替代方法将导致预测差距，因此需要研究其对比较期权的影响。已开发出用于建筑信息建模（BIM）建模工具的插件，以使用各种方法执行BPS。这些方法已针对具有五种设计选项的办公楼进行了测试。参考方法是使用概率方法处理不确定性，详细分区以创建区域以及EnergyPlus预测能量的方法。确定性或ML方法的预测差距较小，比较结果与参考方法相似。简化模型方法的预测差距较大，仅使40％的比较结果与参考方法相似。这些发现对于开发BIM集成工具很有用，可以在早期设计阶段比较各种选择，并确定在时间受限的情况下应采用哪种方法。