Regresar

Self-organizing classification and identification of miscellaneous electric loads

Abstract:

Miscellaneous electric loads (MELs) represent a large portion of the electricity consumption. Economic and environmental impacts of energy consumption lead to needs and opportunities in energy management and saving. This paper proposes an intelligent classification and identification of MELs by extending the Self-Organizing Map (SOM) framework to a supervised manner. The SOM can classify a large amount of MELs data into several clusters by inherent similarities. The self-organizing identifier thus has the advantages of being accurate, robust, and applicable. © 2012 IEEE.

Año de publicación:

2012

Keywords:

  • High energy efficiency buildings
  • load identification
  • classification
  • self-organizing map

Fuente:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Potencia eléctrica
  • Aprendizaje automático

Áreas temáticas:

  • Física aplicada
  • Ciencias de la computación
  • Métodos informáticos especiales

Contribuidores:

Habetler T.G.Habetler T.G.
Harley R.G.Harley R.G.
Jose Alex RestrepoJose Alex Restrepo
Yang Y.Yang Y.
He D.He D.
Du L.Du L.
Lu B.Lu B.