Semantic data modelling with graph databases enabling interoperability in smart gridsDervišević, Amila (Avtor) Zajc, Matej (Mentor) Suljanović, Nermin (Komentor) CIMsmart gridbig dataInternet of Things (IoT)ICTinteroperabilitygraph databaseRDFThe process of digitalisation of the electricity supply chain and introduction of the smart grid as a concept that will facilitate inclusion of renewable energy resources and electrical vehicles into the existing power grid, led to a significant increase of data generation and information exchange between stakeholders. Each stakeholder or entity in the electricity domain can use a different approach to model data which poses a challenge for data interoperability between them. Some business use cases and applications require data from different sources at various locations, making this problem even more difficult. This master thesis addresses the described problem by investigating semantic modelling of electricity data and storing this data in graph databases for further fast and reliable information retrieval. The Common Information Model (CIM) enables semantic interoperability of electricity data related to different process and time scales from real-time to long-term planning (e.g. grid models, measurements, market data etc). Originating from the classification of electricity data, CIM ontology for semantic data modelling is overviewed in this thesis. Since Resource Description Framework (RDF) represents the efficient mean of data serialization on Semantic Web and currently big electricity data is commonly serialized in this format, an effort is given to deep understanding of RDF. In the next step, this thesis investigates methodology for storing data serialized as an RDF/XML file into a graph database as well as approaches for data retrieval from databases requested by other business processes. In order to enable combining electricity data with other data available at Semantic Web (e.g. weather data, Google maps etc), the work presented in this thesis will leverage semantic query languages for electricity data retrieval from database. In the scope of the practical work of this thesis, distribution grid models in RDF format will be deployed in two graph databases with different designs (Neo4j and GraphDB) and their performances with standard KPIs (key performance indicators) for databases will be compared. The master thesis contributes to the overall investigation of semantic data modelling and data interoperability in the electricity domain, as a crucial component for wider deployment of smart grid technologies in the future.[A. Dervišević]20212021-02-20 19:00:01Magistrsko delo/naloga124822UDK: 621.31(043.3)VisID: 51701COBISS_ID: 69298691sl