Data-driven framework for the detection of non-technical losses in distribution grids

Non-technical losses (NTL) occurring in the electric grid, particularly at the distribution level may cause a negative impact on utilities' interest, paying consumers and states. Reducing NTL can increase revenue, profit, reliability, among other aspects of the power system. Therefore, this sub...

Full description

Autores:

De la Hoz Domínguez, Enrique José
Rivera, A.
Botina, K.
Perdomo, G.A
Montoya, O.
Campillo Jiménez, Javier Eduardo

Tipo de recurso:

Fecha de publicación:

2020

Institución:

Universidad Tecnológica de Bolívar

Repositorio:

Repositorio Institucional UTB

Idioma:

eng

OAI Identifier:

oai:repositorio.utb.edu.co:20.500.12585/9954

Acceso en línea:

https://hdl.handle.net/20.500.12585/9954
https://ieeexplore.ieee.org/document/9290186

Palabra clave:

Non-technical losses
Machine learning
Feature selection
Distribution grids
LEMB

Rights

closedAccess

License

http://purl.org/coar/access_right/c_14cb