Proactive and Predictive Maintenance of District Heating Systems

District heating plays an important role in facilitating a transition towards cleaner energy in Denmark. In today’s digital district heating technologies, data validation and reconstruction are either missing or done to a limited extent. This has to change to unleash the full potential of digitalization. Currently, district heating distribution companies take a reactive “wait till it breaks” approach to maintenance which is accompanied by non-efficient planned maintenance. There is an urgent need for smarter and proactive maintenance strategies.

In this project, we will develop a diagnostics tool for automatic and cost-effective data validation and reconstruction, fault and anomaly prediction, detection, and diagnosis in district heating systems. The proposed solution uses data from the existing infrastructure such as smart meters and does not need additional hardware deployment. Furthermore, it will predict faults and anomalies which can pave the way for better asset performance management and planning. The tool enables predictive maintenance which is a more proactive and efficient maintenance strategy than the currently used maintenance approach in the district heating systems.