Application of data analytics for information retrieval from a typical DSO's database

Jelena Ponocko; Jovica V. Milanovic; Robin Preece; N. C. Wooley

doi:10.1109/ISGTEurope.2016.7856314

Application of data analytics for information retrieval from a typical DSO's database

Jelena Ponocko, Jovica V. Milanovic, Robin Preece, N. C. Wooley

Faculty of Science and Engineering

National Grid UK

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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Abstract

This paper introduces the reasons for big data analytics in distribution network studies and potential benefits it could give. Summary of the most common data mining methods used in power system studies is also given, followed by a comparative analysis. A use case is shown at the end in order to present some examples of extraction of useful information from raw data stored in a real distribution utility's database. This was done by using some of the basic data mining methods applied to different types of attributes describing distribution system feeders in 11 kV and 6.6 kV network. The initial results showed that the usefulness of information depends on the level of data aggregation, as well as the choice of data analytics method.

Original language	English
Title of host publication	PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE
Publisher	IEEE
ISBN (Electronic)	978-1-5090-3358-4
ISBN (Print)	978-1-5090-3359-1
DOIs	https://doi.org/10.1109/ISGTEurope.2016.7856314
Publication status	Published - 16 Feb 2017
Event	PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE - Ljubljana, Slovenia Duration: 9 Oct 2016 → 12 Oct 2016

Conference

Conference	PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE
Country/Territory	Slovenia
City	Ljubljana
Period	9/10/16 → 12/10/16

Keywords

Data mining, Databases, Big data, Correlation, Monitoring, Artificial neural networks, Data analysis

Access to Document

10.1109/ISGTEurope.2016.7856314

ISGT2016 Ponocko Application of Data_finAccepted author manuscript, 386 KB

Cite this

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title = "Application of data analytics for information retrieval from a typical DSO's database",

abstract = "This paper introduces the reasons for big data analytics in distribution network studies and potential benefits it could give. Summary of the most common data mining methods used in power system studies is also given, followed by a comparative analysis. A use case is shown at the end in order to present some examples of extraction of useful information from raw data stored in a real distribution utility's database. This was done by using some of the basic data mining methods applied to different types of attributes describing distribution system feeders in 11 kV and 6.6 kV network. The initial results showed that the usefulness of information depends on the level of data aggregation, as well as the choice of data analytics method.",

keywords = "Data mining, Databases, Big data, Correlation, Monitoring, Artificial neural networks, Data analysis",

author = "Jelena Ponocko and Milanovic, {Jovica V.} and Robin Preece and Wooley, {N. C.}",

year = "2017",

month = feb,

day = "16",

doi = "10.1109/ISGTEurope.2016.7856314",

language = "English",

isbn = "978-1-5090-3359-1",

booktitle = "PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE",

publisher = "IEEE",

address = "United States",

note = "PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE ; Conference date: 09-10-2016 Through 12-10-2016",

}

Ponocko, J , Milanovic, JV , Preece, R & Wooley, NC 2017, Application of data analytics for information retrieval from a typical DSO's database. in PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE. IEEE, PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE, Ljubljana, Slovenia, 9/10/16. https://doi.org/10.1109/ISGTEurope.2016.7856314

TY - GEN

T1 - Application of data analytics for information retrieval from a typical DSO's database

AU - Ponocko, Jelena

AU - Milanovic, Jovica V.

AU - Preece, Robin

AU - Wooley, N. C.

PY - 2017/2/16

Y1 - 2017/2/16

N2 - This paper introduces the reasons for big data analytics in distribution network studies and potential benefits it could give. Summary of the most common data mining methods used in power system studies is also given, followed by a comparative analysis. A use case is shown at the end in order to present some examples of extraction of useful information from raw data stored in a real distribution utility's database. This was done by using some of the basic data mining methods applied to different types of attributes describing distribution system feeders in 11 kV and 6.6 kV network. The initial results showed that the usefulness of information depends on the level of data aggregation, as well as the choice of data analytics method.

AB - This paper introduces the reasons for big data analytics in distribution network studies and potential benefits it could give. Summary of the most common data mining methods used in power system studies is also given, followed by a comparative analysis. A use case is shown at the end in order to present some examples of extraction of useful information from raw data stored in a real distribution utility's database. This was done by using some of the basic data mining methods applied to different types of attributes describing distribution system feeders in 11 kV and 6.6 kV network. The initial results showed that the usefulness of information depends on the level of data aggregation, as well as the choice of data analytics method.

KW - Data mining, Databases, Big data, Correlation, Monitoring, Artificial neural networks, Data analysis

U2 - 10.1109/ISGTEurope.2016.7856314

DO - 10.1109/ISGTEurope.2016.7856314

M3 - Conference contribution

SN - 978-1-5090-3359-1

BT - PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE

PB - IEEE

T2 - PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016 IEEE

Y2 - 9 October 2016 through 12 October 2016

ER -

Application of data analytics for information retrieval from a typical DSO's database

Abstract

Conference

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