Anomaly Detection in Smart Grid Data: An Experience Report

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00090404" target="_blank" >RIV/00216224:14330/16:00090404 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/SMC.2016.7844583" target="_blank" >http://dx.doi.org/10.1109/SMC.2016.7844583</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SMC.2016.7844583" target="_blank" >10.1109/SMC.2016.7844583</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Anomaly Detection in Smart Grid Data: An Experience Report

Popis výsledku v původním jazyce

In recent years, we have been witnessing profound transformation of energy distribution systems fueled by Information and Communication Technologies (ICT), towards the so called Smart Grid. However, while the Smart Grid design strategies have been studied by academia, only anecdotal guidance is provided to the industry with respect to increasing the level of grid intelligence. In this paper, we report on a successful project in assisting the industry in this way, via conducting a large anomaly-detection study on the data of one of the power distribution companies in the Czech Republic. In the study, we move away from the concept of single events identified as anomaly to the concept of collective anomaly, that is itemsets of events that may be anomalous based on their patterns of appearance. This can assist the operators of the distribution system in the transformation of their grid to a smarter grid.

Název v anglickém jazyce

Anomaly Detection in Smart Grid Data: An Experience Report

Popis výsledku anglicky

In recent years, we have been witnessing profound transformation of energy distribution systems fueled by Information and Communication Technologies (ICT), towards the so called Smart Grid. However, while the Smart Grid design strategies have been studied by academia, only anecdotal guidance is provided to the industry with respect to increasing the level of grid intelligence. In this paper, we report on a successful project in assisting the industry in this way, via conducting a large anomaly-detection study on the data of one of the power distribution companies in the Czech Republic. In the study, we move away from the concept of single events identified as anomaly to the concept of collective anomaly, that is itemsets of events that may be anomalous based on their patterns of appearance. This can assist the operators of the distribution system in the transformation of their grid to a smarter grid.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

The 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016)

ISBN

9781509018970

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

2313-2318

Název nakladatele

IEEE

Místo vydání

Budapest

Místo konání akce

Budapest

Datum konání akce

9. 10. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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