Water hammer, or hydraulic shock, occurs in pressurized pipelines when fluid flow is abruptly altered, leading to pressure surges. Even though this phenomenon can cause significant damage to systems, it is often overlooked during design phases of district heating (DH) networks. This paper investigates the impact of temperature on water hammer phenomena. Various modeling approaches are discussed, emphasizing the importance of considering both hydraulic and thermal transients. To assess the impact, we modeled and simulated a reference problem involving rapid valve closure in a copper pipe system, considering both cavitating and non-cavitating flow scenarios. The steady-state results show that the pressure head at the downstream end of the pipe increases with temperature due to decreasing density and is independent of the pipe material properties. The transient results reveal that higher temperatures lead to cavitation and more intense pressure peaks, which could be missed without considering thermal-hydraulic phenomena. The analysis of a practical problem involving a 1000 MW DH system in Helsinki showed that using a single wave speed for both supply and return lines underestimates pressure peaks due to partial wave cancellation. In contrast, temperature-dependent wave speeds provide more accurate predictions of pressure wave behavior, highlighting the importance of understanding these effects. Sudden pressure drops can trigger protective measures and lead to cavitation, weakening pipeline integrity over time. The findings underscore the importance of considering temperature-dependent properties in the design, modeling and analysis of DH networks to prevent potential damage and ensure system reliability.

This paper presents challenges in the control of 5GDHC networks and proposes an approach for the robust control design of these networks. Temperatures are low and temperature differences are small in 5GDHC networks, in order to minimise heat losses in the distribution network and directly utilise low-temperature heat sources. Therefore, the robust control design of substations is crucial for stable and efficient operation of 5GDHC networks. We proposed the key steps to obtain a consistent control design that can be verified and tested prior to commissioning of the building substations and network. The design approach was elaborated in a case study in an existing neighbourhood in Haarlem, the Netherlands, constructed in the 1930s to 1970s. This neighbourhood will become independent of natural gas using PVT-rooftop panels, individual heat pumps (HP), a 2-pipe, bi-directional energy flow network operating at ultra-low temperatures and ATES system as a seasonal and daily storage facility.

Buildings can deliver short-term thermal energy storage by utilising the thermal capacity of the building construction and/or by activating the water tanks included in the heating/cooling installation. The flexibility potential of demand management using decentralized thermal energy storage has been quantified in many theoretical modelling studies, and it is considered an essential technology for an affordable energy transition. We have investigated the drivers and barriers to the adoption of demand management in buildings in district heating and cooling systems via a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis and presented 17 elements that shape the current and future application of this concept. The results indicate that the application of the DR concept has left the theoretical studies and moved towards real-life applications. Yet, there is a lack of feasible business models and regulatory frameworks supporting the large-scale application of the concept. Utilities and their customers do not fully understand the benefits of the DR concept; therefore they are reluctant to adopt it outside of the research projects where the test environment is fully controlled and with limited impact and timeline. Therefore, the regulatory framework must be adjusted to allow DHC operators to develop new business models and DR tariffs that will incentivise the customers to deliver flexibility to the system without compromising their comfort and everyday practices and increasing energy poverty.

The energy required for space heating amounts to approximately 68% of the total energy demand of existing buildings in Europe. The heat requirement of a building, and thus its carbon emission, can be lowered by optimizing the supply and return temperature of the heating system. A lower supply temperature enables a wider variety of transition pathways towards sustainable heating with reduced carbon emissions. However, the minimum supply temperature that guarantees acceptable indoor temperatures in existing dwellings during design weather conditions is still unknown. In this study, we determine the minimum supply temperature by fitting a 2 R–2C model to hourly measurement data. The measurement data is obtained from a representative set of 220 existing gas-fired dwellings in the Netherlands. The heating system of each dwelling was equipped with a pulse flowmeter and temperature sensors on both the supply and return side. Additionally, data was collected from the thermostat in the main living room and the gas boiler. The data was supplemented with weather data from a nearby weather station. The data-driven model shows that the minimum supply temperature can be lower than 55 °C for 60% of the dwellings during design weather conditions (i.e., −10 °C in the Netherlands). Moreover, the minimum supply temperature is poorly correlated with general building properties, such as the building typology, construction period or specific annual space heating demand (kWh/(m²yr)). On the contrary, the ratio between the required and installed heat output of the radiators in the heating system is a promising parameter to predict the minimum design supply temperature of an individual dwelling that guarantees an acceptable indoor temperature during design weather conditions.

Future district heating systems (DHS) will be supplied by renewable sources, most of which are limited in temperature and flow rate. Therefore, operational optimization of DHS is required to maximize the use of renewable sources and minimize (fossil) peak loads. In this paper, we present a robust and fast model-predictive control approach to use the thermal mass of buildings as a daily storage without violating temperature constraints. The novelty of this paper includes two elements. First, the focus on an operational control strategy that explicitly accounts for temperature-limited renewable sources, like a geothermal source. Secondly, the optimization problem is formulated as a (nearly) convex optimization problem, which is required for adoption of model-predictive control in practice. The examples show that the peak heating demand can be reduced by 50%, if the thermal inertia of the buildings is used and the heating setpoints are adapted. Furthermore, the operational optimization finds the proper balance between benefits of pre-heating using renewable sources with limited capacity and costs of additional heat losses due to pre-heating.

This study presents convex modeling of drainage pumps so that real-time control systems can be implemented to minimize their energy use. A convex model is built based on pump curves and then used in mixed-integer optimization to allow pumps to be turned on or off. It is implemented as an extension to the open source software package RTC-Tools. The formulation is such that the continuous relaxations of the mixed-integer problem are convex, hence branch-and-bound techniques may be used to find a global optimum. The formulation can be used for variable-speed and constant-speed pumps. There are several possible applications, such as optimization of polder systems, pumped-storage systems, or certain water distribution networks. Finally, an example of the drainage pump is presented to compare the method to current methods and show that energy can be saved by using the proposed method.

Gully pots are essential assets designed to relief the downstream system by trapping solids and attached pollutants suspended in runoff. This study applied a methodology to develop a quantitative gully pot sedimentation and blockage model. To this end, sediment bed level time series from 300 gully pots, spanning 15 months, were collected. A generalised linear mixed modelling (GLMM) approach was applied to model and quantify the accumulation of solids in gully pots and to identify relevant physical and catchment properties that influence the complex trapping processes. Results show that the retaining efficiency decreases as sediment bed levels increase. Two typical silting evolutions were identified. Approximately 5% of all gully pots experienced progressive silting, eventually resulting in a blockage. The other gully pots show stabilising sediment bed levels. The depth of the sand trap, elapsed time since cleaning and the road type were identified to be the main properties discriminating progressive accumulation from stabilising sediment bed levels. Furthermore, sediment bed levels exhibit no residual spatial correlation, indicating that the vulnerability to a blockage is reduced as adjacent gully pots provide a form of redundancy. The findings may aid to improve maintenance strategies in order to safeguard the performance of gully pots.