It seems widely expected that future GISs will have increased analytical capabilities that will take them beyond being efficient display and database management devices. Several attempts have already been made to link existing analytical software to various GISs. However, a problem with all of these attempts is that the user is forced to switch back and forth between the GIS operating environment and the analytical software. In this paper we present a statistical analysis package, STACAS, that runs totally within the operating environment of a GIS and utilizes a command structure that makes running the package transparent to the user of the GIS.

Data centres produce waste heat, which can be utilized in district heating systems. However, the mismatch between data centres’ heat supply and district heating systems’ heat demands limits its utilization. Further, high peak loads increase the operation cost of district heating systems. This study aimed to solve these problems by introducing thermal energy storages. A water tank and a borehole thermal energy storage system were selected as the short-term and long-term thermal energy storage, respectively. Energy, economic, and environmental indicators were introduced to evaluate different solutions. The case study was a campus district heating system in Norway. Results showed that the water tank could shave the peak load by 31% and save the annual energy cost by 5%. The payback period was lower than 15 years when the storage efficiency remained higher than 80%. However, it had no obvious benefits in terms of mismatch relieving and CO2 emissions reduction. In contrast, the borehole thermal energy storage increased the waste heat utilization rate to 96% and reduced the annual CO2 emissions by 8%. However, the payback period was more than 17 years. These results provide guidelines for the retrofit of district heating systems, where data centres’ waste heat is available.