The Smart Grid Semantic Platform: Synergy between IEC Common Information Model (CIM) and Big Data
| Autor: | Carlo Tornelli, Giuseppe Mauri, Emanuele Della Valle, Enea Bionda, Marco Balduini, Davide Della Giustina, Fabrizio Garrone, Marco Brambilla |
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| Rok vydání: | 2019 |
| Předmět: |
Electric power distribution
Computer science business.industry 020209 energy 010401 analytical chemistry Big data Interoperability Cloud computing 02 engineering and technology Semantic data model 01 natural sciences 0104 chemical sciences Smart grid Common Information Model (electricity) 0202 electrical engineering electronic engineering information engineering Systems engineering business Semantic Web |
| Zdroj: | 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). |
| DOI: | 10.1109/eeeic.2019.8783632 |
| Popis: | Recent innovations in Information Technology, Cloud Computing, Big Data analysis, Internet of Things (IoT) and Artificial Intelligence (AI) are enabling technological solutions that were previously unimaginable, or usually available only for big IT companies, with impacts in both industry and services. The demonstrator named Smart Grid Semantic Platform (SGSP) has been created using these technologies integrating several aspects of the management of an electricity distribution network. The services deployed on the platform concern the visualization of the topographic data and electricity grid assets, as well as the processing and displaying of historical data related to the operation of the networks and/or the result of Big Data analysis. This paper demonstrates how useful the synergy is between the standard semantic model of the electric network (IEC CIM 61968) and the historical data of the time series of medium voltage electricity consumption analyzed using a Big Data platform. Specifically it illustrates the realization of a use case about the calculation of a load index of the electric lines. |
| Databáze: | OpenAIRE |
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