The future integration of various energy carriers into a single multi-energy network is crucial for enhancing the flexibility, efficiency, and sustainability of the entire energy system. This challenge is closely linked to the digital transition of networks, as it requires integrated management of data from multiple internal utility systems (GIS, asset management, DMS) as well as data related to different energy carriers.

This paper presents a modular, open-source semantic platform based on international standards for the management and study of multi-energy networks: the Multi Energy Semantic Platform (MESP). The architecture, based on Kubernetes and microservices, ensures synergy between semantic web technologies and big data/machine learning algorithms. To demonstrate the platform’s capabilities, a real case study for the city of Milan is presented.

In this example, the electric distribution network and the district heating network are described using a semantic model (based on IEC CIM), and their exchange points are identified and geographically visualized. Both utilities and researchers can benefit from this open-source platform, which supports the easy integration of innovative AI algorithms and can be adapted according to the needs of specific use cases. Additionally, the MESP can support the management operations of energy communities or small electric cooperatives that cannot afford large investments in terms of financial and human resources.