In the effort to de-carbonize the building stock, heat pumps are increasingly utilized in Switzerland, with 70% of the fast-growing heat pump market using ambient air as heat source. Inexpensive and easy to implement, these heat pumps are, however, less efficient than their ground- or water-source counterparts. In this modeling study, we aim at increasing the efficiency of air-source heat pumps using domestic greywater-contained heat. We assess the performance improvement relative to standard heat pump configurations across various climates, seasons, building envelopes, and domestic hot water consumption patterns. The results show that the annually-averaged coefficient of performance improves by 4.1% on average - ranging from 0.6% to 7.5%. This efficiency gain translates on average to 1.8 kWh/week of compressor electricity savings. Although attractive due to its simplicity, the proposed open-loop configuration - preheating of an external heat source - only leads to moderate performance improvement of air-source heat pumps. Based on these results, we extensively discuss and compare alternative system configurations and identify several fundamental differences in the heat recovery dynamics of each configuration. We show that closed-loop systems - using greywater as direct heat source - show the largest performance improvement potential, although being more expensive and complex to implement.

Heat recovery from wastewater is a robust and straightforward strategy to reduce water-related energy consumption. Its implementation, though, requires a careful assessment of its impacts across the entire wastewater system as adverse effects on the water and resource recovery facility and competition among heat recovery strategies may arise. A model-based assessment of heat recovery from wastewater therefore implies extending the modeling spatial scope, with the aim of enabling thermal-hydraulic simulations from the household tap along its entire flow path down to the wastewater resource recovery facility. With this aim in mind, we propose a new modeling framework interfacing thermal-hydraulic simulations of (i) households, (ii) private lateral connections, and (iii) the main public sewer network. Applying this framework to analyze the fate of wastewater heat budgets in a Swiss catchment, we find that heat losses in lateral connections are large and cannot be overlooked in any thermal-hydraulic analysis, due to the high-temperature, low-flow wastewater characteristics maximizing heat losses to the environment. Further, we find that implementing shower drain heat recovery devices in 50% of the catchment's households lower the wastewater temperature at the recovery facility significantly less – only 0.3 K – than centralized in-sewer heat recovery, due to a significant thermal damping effect induced by lateral connections and secondary sewer lines. In-building technologies are thus less likely to adversely affect biological wastewater treatment processes. The proposed open-source modeling framework can be applied to any other catchment. We thereby hope to enable more efficient heat recovery strategies, maximizing energy harvesting while minimising impacts on biological wastewater treatment.

Thermal-hydraulic considerations in urban drainage networks are essential to utilise available heat capacities from waste- and stormwater. However, available models are either too detailed or too coarse; fully coupled thermal-hydrodynamic modelling tools are lacking. To predict efficiently water-energy dynamics across an entire urban drainage network, we suggest the SWMM-HEAT model, which extends the EPA-StormWater Management Model with a heat-balance component. This enables conducting more advanced thermal-hydrodynamic simulation at full network scale than currently possible. We demonstrate the usefulness of the approach by predicting temperature dynamics in two independent real-world cases under dry weather conditions. We furthermore screen the sensitivity of the model parameters to guide the choice of suitable parameters in future studies. Comparison with measurements suggest that the model predicts temperature dynamics adequately, with RSR values ranging between 0.71 and 1.1. The results of our study show that modelled in-sewer wastewater temperatures are particularly sensitive to soil and headspace temperature, and headspace humidity. Simulation runs are generally fast; a five-day period simulation at high temporal resolution of a network with 415 nodes during dry weather was completed in a few minutes. Future work should assess the performance of the model for different applications and perform a more comprehensive sensitivity analysis under more scenarios. To facilitate the efficient estimation of available heat budgets in sewer networks and the integration into urban planning, the SWMM-HEAT code is made publicly available.

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.

Domestic Hot Water (DHW) systems are large energy consumers in newly-built residential buildings. Mitigation measures involve more efficient hot water appliances and distribution systems, waste heat recovery systems, or changes in consumer habits. However, the implementation of these measures must be investigated carefully, as combinations may lead to unforeseen systemic interactions limiting their potential. In this article, we present tools to identify and optimize these interactions. The WaterHub modules were developed for Material and Energy Flow Analyses (MEFA) of domestic hot water systems. Two modules are available: (i) the WaterHub Modelica library includes models for MEFA system definition, and (ii) The HydroGen Python module provides methods for the stochastic generation of appliance-specific hydrographs, used as input data for the simulation of the system energy and water flows. First, we describe the technical aspects of these modules. Second, we provide an example of how they may be used in a didactic scenario analysis of a heat recovery device.