HeatSync

Challenge

Utility companies have increased investments in new methods for delivering services and have digitized their operations to focus on the use of data. District heating networks are a good example of how data integration and analysis can create value. Therefore, it is surprising that digitalization in heating and cooling networks, compared to the electricity sector, has not gained momentum to the same extent. To ensure that district heating companies can optimize production and delivery, a common data model for sharing data is crucial.

Solution

The project will standardize the sharing of district heating data using a common data model to facilitate effective data exchange and collaboration across sectors. A common data model for district heating data optimizes the data sharing process and increases user-friendliness for both data providers and users. This is because organizations and companies can follow a standardized data model instead of creating individual data structures for each use case. This promotes more efficient data management, enables in-depth analysis of the district heating system, and simplifies the implementation of digital services that benefit district heating customers and support the green transition.

Main Deliverable of the Project

The overall goals of the project are to demonstrate the following:

• Implementation and demonstration of a common data model across different types of district heating companies.
• Implementation and demonstration of a data broker (directory) for easy data access for service providers.
• Three separate use cases that demonstrate commercial applications of the developed technology.
• Show potential savings in both efficiency gains in DKK and reduced CO2 emissions through easier data access.

Impact

The project addresses the lack of consistency in current data management practices among Danish district heating companies, which complicates access to and use of data—representing an untapped potential of over 1 billion DKK annually. The project will mature the data model and the data broker, making them commercially viable after the project period.