Electricity load profile classification using Fuzzy C-Means method

Iswan Prahastono; David J. King; C. S. Ozveren; D. Bradley

doi:10.1109/UPEC.2008.4651527

Electricity load profile classification using Fuzzy C-Means method

Iswan Prahastono, David J. King, C. S. Ozveren, D. Bradley

Department of Games and Arts

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

28 Citations (Scopus)

226 Downloads (Pure)

Abstract

This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.

Original language	English
Title of host publication	43rd International Universities Power Engineering Conference
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	499-503
Number of pages	5
ISBN (Electronic)	9788889884096
ISBN (Print)	9781424432943
DOIs	https://doi.org/10.1109/UPEC.2008.4651527
Publication status	Published - 2008
Event	43rd International Universities Power Engineering Conference - Padova, Italy Duration: 1 Sept 2008 → 4 Sept 2008 Conference number: 43

Conference

Conference	43rd International Universities Power Engineering Conference
Abbreviated title	UPEC 2008
Country/Territory	Italy
City	Padova
Period	1/09/08 → 4/09/08

Keywords

Fuzzy set theory
Load forecasting
Pattern clustering

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10.1109/UPEC.2008.4651527

King_ElectricityLoadProfileClassification_Author_2008Accepted author manuscript, 395 KB

Cite this

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title = "Electricity load profile classification using Fuzzy C-Means method",

abstract = "This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.",

author = "Iswan Prahastono and King, \{David J.\} and Ozveren, \{C. S.\} and D. Bradley",

year = "2008",

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language = "English",

isbn = "9781424432943",

pages = "499--503",

booktitle = "43rd International Universities Power Engineering Conference",

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note = "43rd International Universities Power Engineering Conference, UPEC 2008 ; Conference date: 01-09-2008 Through 04-09-2008",

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T1 - Electricity load profile classification using Fuzzy C-Means method

AU - Prahastono, Iswan

AU - King, David J.

AU - Ozveren, C. S.

AU - Bradley, D.

N1 - Conference code: 43

PY - 2008

Y1 - 2008

N2 - This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.

AB - This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.

U2 - 10.1109/UPEC.2008.4651527

DO - 10.1109/UPEC.2008.4651527

M3 - Conference contribution

SN - 9781424432943

SP - 499

EP - 503

BT - 43rd International Universities Power Engineering Conference

PB - IEEE

CY - Piscataway, NJ

T2 - 43rd International Universities Power Engineering Conference

Y2 - 1 September 2008 through 4 September 2008

ER -

Electricity load profile classification using Fuzzy C-Means method

Abstract

Conference

Keywords

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