Electrical consumers data clustering through Optimum-Path Forest

Author

Ramos, Caio C O ; Souza, André N. ; Nakamura, Rodrigo Y M ; Papa, João P.

Author_Institution

Dept. of Electr. Eng., Univ. of Sao Paulo, São Paulo, Brazil

fYear

2011

fDate

25-28 Sept. 2011

Firstpage

1

Lastpage

4

Abstract

Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter.

Keywords

graph theory; losses; optimisation; power system economics; power system management; Brazilian electric power company; electrical consumer data clustering; illegal consumer; nontechnical losses identification; optimum path forest clustering technique; Clustering algorithms; Companies; Conferences; Context; Feature extraction; Power systems; Support vector machines; Clustering; Non-technical Losses; Optimum-Path Forest; Pattern Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System Application to Power Systems (ISAP), 2011 16th International Conference on

Conference_Location

Hersonissos

Print_ISBN

978-1-4577-0807-7

Electronic_ISBN

978-1-4577-0808-4

Type

conf

DOI

10.1109/ISAP.2011.6082217

Filename

6082217