Energy consumption in the chemical industry is an important operating cost and environmental impact factor and reducing it is also explicitly mentioned as one of the key principles of green chemistry. Energy consumption has thus been included in diverse process design and evaluation tools as a key metric. However, measurements of energy consumption at the process equipment level are scarce, especially in fine chemical production typically performed in multiproduct and multipurpose batch plants. In this work, we present a shortcut approach based on statistical models, such as probability density functions (PDF) and classification trees, for estimating steam consumption which typically represents the highest energy utility consumption in batch plants. The output of these models is in the form of intervals derived from PDF interquartile ranges and as classes derived from the classification trees, respectively. The validation results (i.e., goodness of fit, cross validation, and case studies) show that the models provide satisfactory interval estimations of steam consumption for benchmarking chemical reaction types and performing uncertainty analysis. The models can be primarily used at early design stages for screening purposes, the reaction type being the minimum needed input information, allowing in the case of classification trees also an analysis of the most influencing predictor variables (i.e., reaction type and operating parameters) upon the steam consumption. This study also demonstrates the use of the PDF statistical models to a previously published case study for the production of the intermediate substance 4-(2-methoxyethyl)-phenol, which can be produced from seven different synthesis routes. The ranking of the synthesis routes according to the PDF models shows similar trends to that of an Energy Loss Index proxy indicator which however requires more detailed chemical and process information.

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化工分厂的门到门能耗：基于反应合成类型的统计模型

化学工业中的能耗是重要的运营成本和环境影响因素，降低能耗也被明确提到是绿色化学的关键原则之一。因此，能耗已作为各种关键指标纳入了各种过程设计和评估工具中。但是，在过程设备级别上的能耗测量很少，尤其是在多产品和多用途批处理工厂中通常进行的精细化工生产中。在这项工作中，我们提出了一种基于统计模型的捷径方法，例如概率密度函数（PDF）和分类树，用于估算蒸汽消耗，蒸汽消耗通常代表批处理工厂中最高的能源效用。这些模型的输出分别是从PDF四分位数范围得出的间隔形式和从分类树得出的类的形式。验证结果（即拟合优度，交叉验证和案例研究）表明，该模型提供了令人满意的蒸汽消耗间隔估计，以用于基准化学反应类型和进行不确定性分析。该模型可主要用于早期设计阶段以进行筛选，反应类型是所需的最少输入信息，在分类树的情况下，还可以对影响最大的预测变量（即反应类型和操作参数）进行分析。蒸汽消耗。这项研究还证明了在先前出版的案例研究中使用PDF统计模型来生产中间体物质4-（2-甲氧基乙基）-苯酚，该中间体可以通过七个不同的合成途径生产。根据PDF模型，合成路线的排名显示出与能量损失指数替代指标相似的趋势，但是该指标需要更详细的化学和工艺信息。