Spatial aggregation and visualisation of urban heat demand using graph theory.

Abstract

Because of the physical properties of heat energy, information about the spatial pattern of building heat demand is important for designing climate protection measures in the heating sector (efficiency improvements and renewable energy integration). Many cities in Germany currently prepare ‘heat demand cadastres’ – thematic maps, depicting building heat demand. The growing trend towards open data points into the direction of making these cadastres public, so that different actors can make use of them. However, making such data public may violate the legal requirement of protecting private data. We present a way of tackling this problem with an approach for the aggregation of spatially represented heat demand. Using an algorithm based on graph theory, we group buildings such that the tracing of energetic characteristics and behaviour to individuals is rendered unfeasible. Our method also allows additional constraints to be introduced, for example, aggregating with respect to plot boundaries. We discuss how the building groups can be visualised in a map by presenting a method of generating customised geometries for each group. Finally, we present a visualisation of both specific heat demand (in kWh/(m2*a)) and total heat demand (in kWh/a) in one and the same map. This aids the analysis of more complex questions involving energy efficiency and heat supply.