Decision support tools in the process industry have been gaining relevance, especially for operation under uncertain conditions. This study describes real-time reconciled simulation (RTRS), and analyzes its usefulness as decision-making tool for process operators, especially under unexpected process changes. The proposed methodology is implemented in two case studies in the context of an oil refinery hydrogen network, where both plant and network levels are considered. A what-if analysis is conducted on two case studies, assessing two feasible mitigation actions for each case baseline condition. The focus of the discussion is, nevertheless, on the methodology itself and its general features as decision support tool. The relative error of RTRS for estimation of states and parameters, considering unmeasured disturbances, is satisfactory aligned with industrial standards for online measurements. In terms of mitigation actions, these are assessed with regards to its economic impact on the system in question. It is shown how actions at plant level may be disadvantageous when facing hydrogen demand changes, compared to network-wide mitigation actions. At plant level, it is pointed out the importance of purification units, prevailing over hydrogen make-up for mitigation of demand change. It is highlighted the fact that RTRS complements in a straightforward manner other control operation tools such as model predictive controllers (MPC) and real-time optimizers (RTO). Therefore, it may add to any decision support framework an open-loop component with parameter estimation and forecasting capabilities. Moreover, its potential for training and integration within other tools packages is discussed. Future directions of research are commented such as fully integrated decision support frameworks, including RTRS, MPC and RTO. Additionally, how RTRS may relate to digital twins, including an example of a suitable architecture is introduced, and RTRS role in enterprise-wide decision-making solutions is commented.

流程工业中的决策支持工具越来越重要，尤其是在不确定条件下的操作中。这项研究描述了实时协调模拟（RTRS），并分析了其作为过程操作者的决策工具的有用性，尤其是在意外的过程更改下。拟议的方法是在炼油厂氢气网络的背景下的两个案例研究中实施的，其中既考虑了电厂水平，也考虑了网络水平。在两个案例研究中进行了假设分析，针对每个案例基线条件评估了两种可行的缓解措施。但是，讨论的重点是方法本身及其作为决策支持工具的一般特征。考虑到无法测量的干扰，用于估计状态和参数的RTRS的相对误差，与在线测量的工业标准保持一致。在缓解措施方面，将根据缓解措施对相关系统的经济影响进行评估。结果表明，与全网范围的缓解行动相比，面对氢需求变化时，工厂一级的行动可能不利。在工厂一级，指出了提纯装置的重要性，它在缓解需求变化方面优于氢气补充。需要强调的是，RTRS可以直接补充其他控制操作工具，例如模型预测控制器（MPC）和实时优化器（RTO）。因此，它可以向任何决策支持框架添加具有参数估计和预测功能的开环组件。而且，讨论了其在其他工具包中进行培训和集成的潜力。评论了未来的研究方向，例如完全集成的决策支持框架，包括RTRS，MPC和RTO。此外，介绍了RTRS与数字孪生的关系，包括一个合适架构的示例，并评论了RTRS在企业范围决策解决方案中的作用。