Two dataset created by APROS recording the operational condition variations of IES integrated energy system

Using the APROS software, we set up two IESs: a simpler system comprising a microgrid, a steam network, and a compressed air network, where the steam network powers both the microgrid’s generator and the compressor in the compressed air network through a turbine; and a more complex system that builds on this by adding a district heating system fed by the steam network, along with battery storage and photovoltaic units in the microgrid, and a steam storage tank in the steam network. The datasets primarily consist of time-series data reflecting the status of various IES components, recorded at a 1-second resolution to capture how the system’s equipment states respond to external influences.

The code corresponding to the dataset can be found on GitHub: Lirdon/Structure_Optimized_Temporal_Adapted_Graph_Learning: Structure_Optimized_Temporal_Adapted_Graph_Learning (SOTA!)