"Prescriptive Analytics Tool" til fjernvarmenet

Denmark's energy system depends on district heating, which provides a reliable heating supply and supports the country's sustainable energy goals. However, the current reactive and preventive approaches to fault management, maintenance, and renovations in district heating networks are inefficient and costly. Developing smarter tools for maintenance and planning is necessary.

This project develops and demonstrates a Prescriptive Analytics Tool for District Heating Networks. The tool enables cost-effective Condition Assessment and Prediction that is currently missing for district heating networks. This is done through the development of data-driven and physics-based digital twins that combine the available thermographic image sequences of district heating networks with data from already existing infrastructure such as smart meters, GIS, etc. to provide actionable insights about the operation and maintenance of the network. In addition, the Prescriptive Analytics Tool uses these insights together with information on the available resources to automatically generate the optimal Maintenance/Renovation Plan through mathematical optimization. The proposed tool not only improves maintenance strategies in DH networks but also contributes to cost and energy efficiency improvements, maximizing asset life, operational performance, or uptime, optimizing maintenance/renovation operations, and will set the stage for the creation of a self-healing district heating system in the future. Pilot tests and demonstration of the tool will happen in collaboration with two Danish district heating companies, Hofor A/S and Frederiksberg Forsyning A/S, while commercialization of the tool will be driven by Drone Systems, a leading specialist in thermal drone inspections in Denmark with collaboration with NIRAS A/S.