One third of the global carbon emissions are emitted by the building sector. Over the last decades, space heating loads have decreased in modern buildings, and domestic hot water (DHW) is now oftentimes the largest energy consumer in the household. We developed the WaterHub modeling framework to assess the potential of technologies or measures targeting DHW energy demand. The framework combines process-based technological models and stochastic water demand modeling in a modular way to allow for holistic simulations of complex DHW systems. In two rigorous tests of the modeling framework, we demonstrated the importance of water consumption dynamics in the modeling of DHW systems, showing that static modeling leads to underestimated heat losses and wrong energy consumption predictions. In an exemplary case study, we identified and quantified the synergistic interactions between water boiler temperatures and a drain water heat recovery device, demonstrating the strength of this methodology for optimizing strategies targeting DHW systems. With its modular structure, this open-source modeling framework can be extended to include any DHW-related technology, providing a useful common platform for collaboration between technology developers and water experts.

全球碳排放量的三分之一是建筑部门排放的。在过去的几十年中，现代建筑中的空间供暖负荷有所减少，而生活热水（DHW）现在通常是家庭中最大的能源消耗者。我们开发了WaterHub建模框架，以评估针对DHW能源需求的技术或措施的潜力。该框架以模块化的方式将基于流程的技术模型和随机需水模型结合在一起，以对复杂的DHW系统进行整体仿真。在建模框架的两次严格测试中，我们证明了耗水动力学在DHW系统建模中的重要性，表明静态建模会导致热量损失低估和能耗预测错误。在一个示例性案例研究中，我们确定并量化了热水锅炉温度与排水热回收装置之间的协同作用，证明了该方法对于针对DHW系统进行优化策略的优势。凭借其模块化结构，该开源建模框架可以扩展为包括与DHW相关的任何技术，从而为技术开发人员与水专家之间的协作提供了有用的通用平台。