Optimisation of district heating Smart Grid systems at low temperatures

District heating covers more than 60 % of the heat consumption of Danish housings, and the Danish

export of installation components related to district heating is increasing. The political target is to increase

the use of renewable energy in Denmark.

To enable an efficient use of renewable energy sources in a district heating system it is essential to have a

detailed knowledge of the different operating parameters and the dynamics in the system including

knowledge of the consumption pattern. At present, a large number energy consumption meters, ”Smart

Meters”, enabling remote reading are installed across the country. These meters are able to provide

extensive data with a high degree of resolution in time. This offers a unique possibility to gain insight into

the dynamics in the district heating network and the consumer behaviour and to use this information for

optimising the performance of the network. This will result in considerable energy savings. However, a

challenge in this respect is to analyse and process this amount of data to enable it to be used by the

simulation software that is traditionally used for performance optimisation in district heating systems.

AffaldVarme Aarhus has established two test areas where 78 remote read Smart Meters are installed.

These meters can read out data in minute intervals which is an exceptional high sampling rate. The large

amount of data generated by these unique meters provides a special opportunity to analyse the

performance of the network and the consumption patterns and to test performance optimising modelling

strategies with high time resolution.

The objective of the project is therefore – by using these testing possibilities – to develop a method that

incorporates the large data set in a generic modeling strategy to be used together with existing hydraulic

modeling tools. A generic model of the dynamical behaviour of the distribution network that includes

consumption patterns is made. By means of the developed modelling strategy the further objective is to

analyse changes in the operating conditions and the potential energy savings using different optimisation

measures.

Therefore, the project comprises the following activities:

• Modelling strategies

• Lowering of the mean supply temperature to the lowest possible level for the test area

• Testing of special adapted district heating units installed at a number of consumers

• Testing of automatic shunt valves

The outcome of the project is optimised modelling strategies for Smart Grid systems and detailed

assessments of the potential performance optimisation using different optimisation strategies. Through this

work the involved companies will get a unique knowledge to be used in the further development of

components for use in future Smart Grid systems.