既有建筑能源改造实践中，改造参数的不确定性对改造结果的影响显著。为了支持能源改造决策，提出结合拉丁超立方抽样的蒙特卡洛方法评估不同改造方案，采用树状高斯方法筛选影响改造过程的关键变量。结果表明，不确定分析可以在改造设计初级阶段量化评估改造方案，两种典型改造场景的节能率分别在32.7%~55.2%和55.5%~108.4%波动，节能效果好的改造方案不确定性高；使用累积概率分布评估改造成功的概率，满足改造目标概率分别为58%和96.4%，可再生能源技术的加入保证了改造结果；敏感性分析结果表明，渗透率和设备功率密度是办公建筑能源消耗的最重要因素，占输出方差的80%。研究结果对建筑节能改造方案的选择提供了理论依据和方法借鉴。

In the practice of energy renovation of existing buildings, the uncertainty of renovation parameters has a significant impact on the renovation results. To support energy renovation decision-making, a Monte Carlo method combined with Latin hypercube sampling was proposed to evaluate different renovation schemes, and a tree-based Gaussian method was used to screen key variables that affect the renovation process. The results show that uncertainty analysis can quantitatively evaluate renovation schemes at the preliminary design stage. The energy-saving rates of two typical renovation scenarios fluctuate between 32.7% ~ 55.2% and 55.5% ~108.4%, respectively, with higher uncertainty in schemes with better energy-saving effects. The cumulative probability distribution was used to assess the probability of renovation success, with the probabilities of meeting renovation targets being 58% and 96.4%, respectively. The integration of renewable energy technologies ensures the renovation results. Sensitivity analysis results show that infiltration rate and equipment power density are the most important factors in office building energy consumption, accounting for 80% of the output variance, which provides a theoretical basis and methodological reference for the selection of more building energy renovation schemes in the future.