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.

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.