Abstract
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.
Highlights
Buildings are the largest energy consumers in the world, resulting in approximately one third of the global carbon emissions [1]
Because events from the semi- and fully-stochastic scenarios have lower inter-event time intervals – i.e. a higher frequency, these results suggest that event frequency is the main driver for heat losses dynamics in the system
Our interpretation of the discrepancies – resulting from the dynamic modeling approach – is in line with results from Kenway et al [20], who recently presented a model for dynamic simulations of shower events. They conclude, as we do, that heat losses from hot water pipes can only be accurately simulated with the help of a dynamic model. This statement can be generalized, as our results show that dynamic simulations of all water-related processes in households are critical for accurate assessments of the water-energy nexus
Summary
Buildings are the largest energy consumers in the world, resulting in approximately one third of the global carbon emissions [1]. Remarkable efforts towards sustainable buildings has led to major improvements to reduce the primary energy consumption for space heating. Modern single family buildings consume 65% less energy for heating than constructions from the 1970s [2]. Recent buildings oftentimes consume more energy for DHW than for space heating (up to 2-fold in Minergie-P buildings) [3,4]. One can (i) reduce the primary energy consumption using energy-efficient or heat recovery systems. At district or regional level, one can (iii) recover heat from sewers or wastewater treatment plant effluents, reducing the net energy consumption of the urban water cycle [5]
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