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Paper RSE 16003857

Integration of Power Quality information in the framework of a standard semantic model

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IEEE EEEIC 16th IEEE International Conference on Enviroment and Electrical Engineering Firenze, 7-10 , Giugno-2016.

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E. Bionda (RSE SpA), D. Pala (RSE SpA) , G. Proserpio (RSE SpA), L. Tenti (RSE SpA), S. Pugliese (A2A Reti Elettriche S.p.A), D. Della Giustina (A2A Reti Elettriche S.p.A)

SMART-DSYS 2016 - Development and management of distribution networks

In this work IEC CIM standard has been adopted as a reference model for the integration of data from the Power Quality monitoring of medium voltage distribution networks and, more in particular from the QuEEN system, to demonstrate the possible synergies between these last with the information already provided by the reference model (network topologies, cartographic information). In perspective this integration could be leveraged also in the framework of the Big data and Open Linked Data Paradigm.

The exploitation of the growing amount of information produced by systems is often associated with the paradigm of Big Data. Next to this approach it remains the interest in integrating information of different origin within a shared framework, conceptually formalized by an ontology. The IEC Common Information Model (CIM) is a natural candidate to take on the role of reference ontology in the electrical context being able to describe different types of electrical domain information (eg. topologies of electrical networks, market information, metering, etc.. ) in an integrated way. The activities described here have adopted the CIM standard as a reference for the integration of information gathered from Power Quality (PQ) monitoring of medium voltage distribution networks, in order to demonstrate the possible synergies with the types of information already provided in that reference model, namely those associated with topologies network, and cartographic information. The result of this integration could be in perspective leveraged in the frame of the Big Data and the Open Linked Data paradigm.

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