Dear Reader,

For the 43rd issue of our heatbeat Research Newsletter, we are focusing entirely on the advanced control of district heating networks. To this end, we are presenting three new articles that show different ways of optimizing the operation of district heating networks and, in particular, the connected buildings. In addition to increased energy efficiency, new business models can also be established in the district heating sector. In the first article, model-predictive controllers are used to introduce demand-side management and demonstrate the effects of this on district heating networks. The second article tests just this type of intervention using real examples. The last article focuses on the operation of bi-directional heating networks and also uses model predictive controllers for this purpose.

Effects of Demand Side management on District Heating Networks

The model predictive control of heating systems (or MPCl) has the potential to optimize the use of energy, peak loads and thermal comfort in rooms. From the perspective of the district heating network, for example, large load peaks can be avoided by coordinating several buildings. This is exactly what is discussed in the article by H. Hakansson et al. "Effects on district heating networks by introducing demand side economic model predictive control" .

The results show that in the future (thermal insulation + expansion of heating networks) a heat demand of around 30 TWh/a can be expected in heating networks in Denmark. Around 20 % of this can be covered by industrial waste heat sources capable of meeting base loads. Only waste heat sources above 60 °C were taken into account here, so that there is even higher potential in combination with heat pumps. Around half of the district heating systems examined have usable geothermal sources in the direct surroundings of the heating network.

Testing demand side management strategies on real buildings

A very common disadvantage of the findings presented above is that they can usually only be demonstrated simulatively and the actual effects in the buildings for different demand-side management interventions are not tested in real life. A. Mohammadnia et al. would like to make a decisive contribution to this with the article "Feasibility assessment of next-generation smart district heating networks by intelligent energy management strategies" .

A total of nine typical strategies for advanced controls for buildings connected to district heating networks are being tested. The strategies range from switching off the output over a short period of time, to reducing the output by lowering the flow temperature, to preheating the buildings using a higher output and combining the variants. Each strategy is tested on a real building for around seven days in three different buildings. Both the indoor temperatures and the heat consumption in individual rooms of the buildings are measured. It is shown that the targeted reduction of the flow temperature in particular has great potential for shifting peak loads in the district heating network, reduces the buildings' heating requirements and yet does not result in any significant loss of thermal comfort. The results are important for the future integration of modern demand side management controls.

MPC controls for bidirectional heating networks

We have already described the advantages and disadvantages of bidirectional heating networks and how they work in several newsletters. For these district heating networks, it is particularly important that the later control system is well designed in terms of both energy and hydraulics. Optimized operation should be taken into account at the design stage. L. Frison et al. make a proposal for model predictive control of these heating networks in the article "Model predictive control of bidirectional heat transfer in prosumer-based solar district heating networks"

The special aspect of this work is that the model-predictive controller is compared with the real operation of a bidirectional district heating network. The district heating network consists of a central heating plant and 37 buildings, all of which are equipped with solar thermal systems and buffer storage tanks. The buildings can both draw heat from the heating network and feed in surplus heat from the solar thermal systems. If all heat flows and possible situations are to be covered, this results in a complex control problem, which is solved with an innovative approach in the work presented here. The comparison of the new control approach with real operation is very impressive. It is described that up to 75 % of the heat previously fed in centrally can be saved in summer by the control system. Thanks to the predictive control, the decentralized storage tanks can be charged and discharged in a more specific manner, thus making better use of the solar thermal potential.

Further information

As always, we recommend the three articles in full length. The large number of new publications addressing the topic of control in district heating networks shows that there is still great potential here, which must be exploited in existing and new district heating networks.

The next issue of our newsletter will be published on June 5, 2024.