Building energy estimation for the building sector under various scenarios are needed for building energy regulation and policy making. This often starts with representative baselines (either empirical baseline or modeled baseline). Commercial Buildings Energy Consumption Survey (CBECS) data is a widely used empirical baseline for U.S. commercial buildings, but none of the existing baseline model are developed to represent the CBECS data. This paper aims to develop new baseline models for the U.S. medium office buildings, which can produce modeled baselines consistent with the CBECS data. First, we introduced the methodology to create baseline models and the criteria to evaluate the performance of baseline models. The methodology consists of three phases: (1) identification of model inputs, (2) model calibration, and (3) model validation with uncertainty analysis. The evaluation index is the coefficient of variation of the root-mean-square deviation (CV(RMSD)) of site energy use intensities (EUIs) between the modeled baseline and empirical baseline. Then 30 new baseline models for two vintages (pre- and post-1980) and 15 climate zones were created. The evaluation shows that the CV(RMSD) is lower than 0.05 for the modeled baselines produced by the new baseline models. As a comparison, the CV(RMSD) is higher than 0.1 for the existing modeled baselines generated by DOE Commercial Reference Building Models. Further analysis shows that the new baseline models are able to capture the uncertainties of the representative features of existing buildings.

建筑能耗监管和政策制定需要在各种情况下针对建筑行业的建筑能耗估算。这通常从代表性基线（经验基线或建模基线）开始。商业建筑能耗调查（CBECS）数据是美国商业建筑广泛使用的经验基准，但没有开发现有的基准模型来表示CBECS数据。本文旨在为美国中型办公楼开发新的基准模型，该模型可以产生与CBECS数据一致的基准模型。首先，我们介绍了创建基线模型的方法和评估基线模型性能的标准。该方法包括三个阶段：（1）识别模型输入，（2）模型校准，（3）通过不确定性分析进行模型验证。评价指标是建模的基准线与经验基准线之间的站点能源使用强度（EUI）的均方根偏差（CV（RMSD））的变化系数。然后创建了两个年份（1980年前和之后）和15个气候带的30个新基准模型。评估显示，新基线模型生成的建模基线的CV（RMSD）低于0.05。相比之下，DOE商业参考建筑模型生成的现有建模基准的CV（RMSD）高于0.1。进一步的分析表明，新的基线模型能够捕获现有建筑物代表性特征的不确定性。