In electrical engineering, event-driven metering is a paradigm enabling different information coding with respect to the conventional time-domain metering techniques. It supplies unevenly spaced time series of compressed data representing energy measurements. This paper discusses about the data- and knowledge-representation of energy-based data in Low Voltage segments of Smart Grids. A representation based on tri-vectors and four-vectors is introduced to represent non-uniform linear time finite elements in unevenly spaced time series of metering data. The proposed representation is based on an original interpretation of process orientation in terms of accumulated energy. Practical examples taken from the data gathered from a new event-driven metering device are shown.

Knowledge Representation for Event-Driven Metering / Simonov, Mikhail; Chicco, Gianfranco; Zanetto, Gianluca. - STAMPA. - (2015), pp. 6-11. (Intervento presentato al convegno Ninth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2015) tenutosi a Blumenau, Brazil nel 8-10 July 2015) [10.1109/CISIS.2015.6].

Knowledge Representation for Event-Driven Metering

CHICCO, GIANFRANCO;
2015

Abstract

In electrical engineering, event-driven metering is a paradigm enabling different information coding with respect to the conventional time-domain metering techniques. It supplies unevenly spaced time series of compressed data representing energy measurements. This paper discusses about the data- and knowledge-representation of energy-based data in Low Voltage segments of Smart Grids. A representation based on tri-vectors and four-vectors is introduced to represent non-uniform linear time finite elements in unevenly spaced time series of metering data. The proposed representation is based on an original interpretation of process orientation in terms of accumulated energy. Practical examples taken from the data gathered from a new event-driven metering device are shown.
2015
978-1-4799-8870-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2666877
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