Title :
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
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;
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
DOI :
10.1109/ISAP.2011.6082217
