New electricity metering devices operating within the distribution networks originate data flows. Metering data are created at remote locations and processed somewhere else. The term “Data” denotes a substance, almost all useful data are “given” to us either by nature, as a reward for careful observation of physical processes, or by other people, usually inadvertently. By the term “Big Data,” we mean the enormous volume, velocity, and type of data that come from different application fields and have the potential to be turned into business value. More and more companies store great amounts of data and its volume is expanding at a terrifying rate in today’s hyperconnected world where people and businesses are creating more and more data every day. For example, very frequent metering—up to subsecond sampling—depicts the true picture about the energy dynamics in power system. Big Data issue concerns: (a) complexity within the data set; (b) amount of value that can be derived from optimized and not analysis techniques; and (c) support data for the analysis. One could describe “big” in terms of the number of useful permutations of sources making useful querying difficult (such as the sensors in an aircraft) and complex interrelationships making cleaning data difficult. We can consider two primary attributes. However, the term “Big” refers to big complexity rather than big volume. Usually relevant and complex data sets of this sort tend to grow rapidly and so Big Data quickly becomes truly astronomical.

Big data application: Analyzing real-time electric meter data / Simonov, M.; Caragnano, G.; Mossucca, L.; Ruiu, P.; Terzo, O.. - (2013), pp. 449-481. [10.1201/b16014]

Big data application: Analyzing real-time electric meter data

Ruiu P.;
2013-01-01

Abstract

New electricity metering devices operating within the distribution networks originate data flows. Metering data are created at remote locations and processed somewhere else. The term “Data” denotes a substance, almost all useful data are “given” to us either by nature, as a reward for careful observation of physical processes, or by other people, usually inadvertently. By the term “Big Data,” we mean the enormous volume, velocity, and type of data that come from different application fields and have the potential to be turned into business value. More and more companies store great amounts of data and its volume is expanding at a terrifying rate in today’s hyperconnected world where people and businesses are creating more and more data every day. For example, very frequent metering—up to subsecond sampling—depicts the true picture about the energy dynamics in power system. Big Data issue concerns: (a) complexity within the data set; (b) amount of value that can be derived from optimized and not analysis techniques; and (c) support data for the analysis. One could describe “big” in terms of the number of useful permutations of sources making useful querying difficult (such as the sensors in an aircraft) and complex interrelationships making cleaning data difficult. We can consider two primary attributes. However, the term “Big” refers to big complexity rather than big volume. Usually relevant and complex data sets of this sort tend to grow rapidly and so Big Data quickly becomes truly astronomical.
9781466578388
Big data application: Analyzing real-time electric meter data / Simonov, M.; Caragnano, G.; Mossucca, L.; Ruiu, P.; Terzo, O.. - (2013), pp. 449-481. [10.1201/b16014]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/300977
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