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Paper RSE 16081817

A demonstrator tool to provide the network operator with micro-services based on big data and semantic web technologies

Paper

International Conference on Renewable Energies and Power Quality (ICREPQ'17) 4-6 ISSN 2172-038 X, vol. 15, Aprile-2017.

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H. Shadmehr (RSE SpA), F. Belloni (RSE SpA) , R. Chiumeo (RSE SpA) , D. Della Giustina (UNARETI S.P.A. RETI ELETTRICHE), D. Pala (RSE SpA) , L. Tenti (RSE SpA), G. Proserpio (RSE SpA), S. Pugliese (UNARETI S.P.A. RETI ELETTRICHE), E. Bionda (RSE SpA)

SMART-DSYS 2017 - Development and Management of Distribution Networks

The paper presents a demonstrator tool, designed as an architecture of microservices, to visualize and correlate Power Quality (PQ) and metering data with topological, cartographic and meteorological information, using both the Semantic Web and the Big Data techniques.

The paper presents a demonstrator tool, designed as an architecture of microservices, to visualize and correlate Power Quality (PQ) data with topological, cartographic and meteorological information. Starting from a single web access point, the tool allows a network operator to “cast a glance” to different kind of data, involved in the management of its network or coming from open data sets, to investigate possible correlations among them. The adopted approach in data management make use of both the ontological and big data paradigma.

This choice allows the operator to manage and correlate large volume of data of different kind (structured and unstructured data). The adopted ontology is the IEC Common Information Model (CIM), which allows the integration of PQ information recorded by the QuEEN monitoring system, at the HV/MV stations of the DSO Unareti S.p.A., with the associated distribution network topology. Services offered regard: (i) the visualization of PQ indices in association with topological and cartographic information; (ii) a classifier, based on a Software Vector Machine (SVM) algorithm, to define the origin of voltage dips; (iii) a web application, developed in the Spark framework, to correlate in space and time QuEEN voltage dips times series with storm cells.

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