Big Data Platform for Smart Grids Power Consumption Anomaly
Detection

D 2019

Big Data Platform for Smart Grids Power Consumption Anomaly Detection

LIPČÁK, Peter, Martin MACÁK a Bruno ROSSI

Základní údaje

Originální název

Big Data Platform for Smart Grids Power Consumption Anomaly Detection

Autoři

LIPČÁK, Peter (703 Slovensko, domácí), Martin MACÁK (703 Slovensko, domácí) a Bruno ROSSI (380 Itálie, garant, domácí)

Vydání

New York, Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, od s. 771-780, 10 s. 2019

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Kód RIV

RIV/00216224:14610/19:00110103

Organizační jednotka

Ústav výpočetní techniky

ISBN

978-1-5386-8005-6

DOI

http://dx.doi.org/10.15439/2019F210

UT WoS

000591782800108

Klíčová slova anglicky

Computer architecture; Big Data; Smart meters; Real-time systems; Power demand; Energy management; Anomaly detection

Štítky

firank_B, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 30. 3. 2020 17:03, Bruno Rossi, PhD

Anotace

V originále

Big data processing in the Smart Grid context has many large-scale applications that require real-time data analysis (e.g., intrusion and data injection attacks detection, electric device health monitoring). In this paper, we present a big data platform for anomaly detection of power consumption data. The platform is based on an ingestion layer with data densification options, Apache Flink as part of the speed layer and HDFS/KairosDB as data storage layers. We showcase the application of the platform to a scenario of power consumption anomaly detection, benchmarking different alternative frameworks used at the speed layer level (Flink, Storm, Spark).

Návaznosti

EF16_013/0001802, projekt VaV

Název: CERIT Scientific Cloud

LM2015085, projekt VaV

Název: CERIT Scientific Cloud (Akronym: CERIT-SC)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, CERIT Scientific Cloud

Citovat

LIPČÁK, Peter, Martin MACÁK a Bruno ROSSI. Big Data Platform for Smart Grids Power Consumption Anomaly Detection. Online. In Proceedings of the 2019 Federated Conference on Computer Science and Information Systems. New York: IEEE, 2019, s. 771-780. ISBN 978-1-5386-8005-6. Dostupné z: https://dx.doi.org/10.15439/2019F210.

@inproceedings{1544717,
   author = {Lipčák, Peter and Macák, Martin and Rossi, Bruno},
   address = {New York},
   booktitle = {Proceedings of the 2019 Federated Conference on Computer Science and Information Systems},
   doi = {http://dx.doi.org/10.15439/2019F210},
   keywords = {Computer architecture; Big Data; Smart meters; Real-time systems; Power demand; Energy management; Anomaly detection},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {New York},
   isbn = {978-1-5386-8005-6},
   pages = {771-780},
   publisher = {IEEE},
   title = {Big Data Platform for Smart Grids Power Consumption Anomaly Detection},
   url = {https://ieeexplore.ieee.org/document/8859779},
   year = {2019}
}

TY  - JOUR
ID  - 1544717
AU  - Lipčák, Peter - Macák, Martin - Rossi, Bruno
PY  - 2019
TI  - Big Data Platform for Smart Grids Power Consumption Anomaly Detection
PB  - IEEE
CY  - New York
SN  - 9781538680056
KW  - Computer architecture
KW  - Big Data
KW  - Smart meters
KW  - Real-time systems
KW  - Power demand
KW  - Energy management
KW  - Anomaly detection
UR  - https://ieeexplore.ieee.org/document/8859779
L2  - https://ieeexplore.ieee.org/document/8859779
N2  - Big data processing in the Smart Grid context has many large-scale applications that require real-time data analysis (e.g., intrusion and data injection attacks detection, electric device health monitoring). In this paper, we present a big data platform for anomaly detection of power consumption data. The platform is based on an ingestion layer with data densification options, Apache Flink as part of the speed layer and HDFS/KairosDB as data storage layers. We showcase the application of the platform to a scenario of power consumption anomaly detection, benchmarking different alternative frameworks used at the speed layer level (Flink, Storm, Spark).
ER  -

LIPČÁK, Peter, Martin MACÁK a Bruno ROSSI. Big Data Platform for Smart Grids Power Consumption Anomaly Detection. Online. In \textit{Proceedings of the 2019 Federated Conference on Computer Science and Information Systems}. New York: IEEE, 2019, s.~771-780. ISBN~978-1-5386-8005-6. Dostupné z: https://dx.doi.org/10.15439/2019F210.

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