Reuse of waste heat: Graph-based algorithms for spatio-temporal optimization of thermal networks

District heating systems are a clean and affordable solution to heat thousands of buildings in Denmark and Europe. Their sustainability depends on their efficiency and on their ability to decarbonize heat generation. Integrating excess heat sources is key to achieving this, but they should be economically viable and reliable, possibly requiring investments in energy storage. However, their temporal variability together with the spatial arrangement of the network's elements makes planning these improvements challenging. Current engineering methods struggle with this complexity and scale. This project will bridge this gap by employing techniques designed for large-scale networks, such as social networks, to this problem. Using data from the Aarhus district heating system we will construct a temporal graph from the data, detect the parts of the network to enhance, and enable engineering-informed optimization for accurate identification of exploitable CO2 reduction opportunities.