Low-temperature thermal grids with surplus heat utilization

Approximately half of buildings' energy demand is related to heating and cooling. At the same time, there are numerous waste heat sources in the cities - such as data centers, large sports facilities and shopping centers - that could be utilized to supply heat to the buildings. District heating enables an economic exploitation of such energy sources that would otherwise be wasted to cover the buildings' heating demands. Today's district heating networks, however, use a high temperature level in the distribution of heat, which leads to high distribution losses, and inefficient utilization of waste heat and renewable heat sources. As it is impossible to lower the supply temperature in the entire district heating network due to existing customers with high-temperature demands, the transition to low-temperature district heating must start from local low-temperature thermal grids (LTTGs) for new building areas. A local thermal grid that utilizes multiple heat sources is a complex system. In LTTG+, dynamic modelling was applied to evaluate different system solutions for selected areas with regards to e.g. heat sources and supply temperature level, as well as to develop control strategies for minimizing peak load demands. The project was carried out in collaboration with a broad consortium consisting of district heating suppliers, municipalities, property companies and researchers from three different cities: Trondheim, Gjøvik and Oslo. The project has focused on two planned building areas: Leangen in Trondheim, with waste heat available from an ice rink; and Furuset in Oslo, where the plan is to utilize the surplus heat available in the DH network in the summer, stored in a large borehole thermal energy storage. For Leangen, a concept based on a low-temperature heating network using waste heat from the ice rink for space heating and heat from greywater for tap water heating was proposed. This concept was evaluated in detail in a spin-off project funded by Enova. For Furuset, a dynamic model for the borehole thermal energy storage was developed in collaboration with KSP project RockStore. The model has been used to evaluate optimal operating strategies for charging and discharging of heat to get the most out of the borehole park. Dynamic modelling was also applied to develop predictive control strategies for customer substations in district heating networks. Today's customer substations use weather compensated control, i.e., the supply temperature to the radiators in a building is based on the outdoor temperature. The simulation results from the project show that switching to predictive control can provide the opportunity to shift heat loads in a building to a low-load period in the district heating network, and consequently reduce the overall and peak energy consumption without affecting the occupants' thermal comfort.

Project outcomes include interdisciplinary collaboration in the national projects KPN RockStore and the FME ZEN; international collaboration in the IEA-funded project CASCADE - A comprehensive toolbox for integrating low-temperature sub-networks in existing DH networks; as well as a spin-off project for detailed evaluation of the suggested low-temperature thermal grid solution for Leangen in Trondheim. The main impacts are reduced primary energy demand and emissions from buildings' heat supply, obtained through increased utilization of waste heat in low-temperature thermal grids. Potential outcomes and effects include the uptake of control strategies for optimal shift of building heat loads for reduced peak heating, thus reduced emissions, and a novel grey water heat recovery solution for domestic hot water heating. Grey water is a stable heat source that is available everywhere, and a robust technology for recovering this heat has potential for wide-spread application.

District heating (DH) will play an important role in the future fossil-free energy systems by enabling economical utilization of energy sources that would otherwise be wasted to cover buildings' heating demands. A prerequisite for this is a reduction in the distribution temperature and a shift towards decentralized heat production. It is however impossible to lower the supply temperature in the entire DH network due to existing customers with high temperature demands. The transition to low-temperature DH must hence start from new building areas. The objective of the project LTTG+ is to develop new knowledge to design and operate cost-effective and flexible local low-temperature thermal grids (LTTGs) with surplus heat utilization and thermal energy storage (TES). A local heating grid that utilizes multiple heat sources and TES, exchanging heat with the primary DH grid, is a complex system. Modelling and simulation is needed to find the most optimal solutions regarding operation and design of the grid and its components. In LTTG+, dynamic modelling will be applied to study the heat flows between buildings, heat suppliers and storage for defined case areas in three cities in Norway: Oslo, Trondheim and Gjøvik. Covering the peak heating demands in a cost-efficient and environmentally manner is one of the major challenges for DH operators. A properly designed decision-support system may significantly improve the economics of operation, model predictive control (MPC) being often the preferred control strategy. In LTTG+, optimization-based predictive control strategies will be developed minimize the peak heating demands in the local grid as well as in the primary DH grid. LTTG+ will build national knowledge required for the transition to low-temperature DH, including knowledge for integration of surplus heat sources; optimal design, sizing and control of LTTGs; as well as interaction with local thermal grid and the primary DH network.