Nowadays, non-intrusive load monitoring (NILM) systems represent an effective alternative to monitoring individual appliances' consumption, avoiding the costs and spatial constraints imposed by the installation of additional sensors. Modern artificial intelligence algorithms, such as machine learning algorithms, make it possible to split the aggregate power absorption profile of a user into the individual power absorption profiles of the main household appliances. However, there is still no full awareness of how these systems can be used effectively and in what situations they can provide consistent support. This paper illustrates the most promising management, diagnostics, and automation activities that can be carried out with the help of an efficient NILM system, referring to the most significant works in literature. A discussion of challenges and future research directions is also provided.

State of art overview of Non-Intrusive Load Monitoring applications in smart grids

Bucci, Giovanni;Ciancetta, Fabrizio;Fiorucci, Edoardo;Mari, Simone
;
Fioravanti, Andrea
2021-01-01

Abstract

Nowadays, non-intrusive load monitoring (NILM) systems represent an effective alternative to monitoring individual appliances' consumption, avoiding the costs and spatial constraints imposed by the installation of additional sensors. Modern artificial intelligence algorithms, such as machine learning algorithms, make it possible to split the aggregate power absorption profile of a user into the individual power absorption profiles of the main household appliances. However, there is still no full awareness of how these systems can be used effectively and in what situations they can provide consistent support. This paper illustrates the most promising management, diagnostics, and automation activities that can be carried out with the help of an efficient NILM system, referring to the most significant works in literature. A discussion of challenges and future research directions is also provided.
File in questo prodotto:
File Dimensione Formato  
measurement sensors 2 mari.pdf

accesso aperto

Descrizione: versione finale
Tipologia: Documento in Versione Editoriale
Licenza: Dominio pubblico
Dimensione 305.84 kB
Formato Adobe PDF
305.84 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/172694
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 19
  • ???jsp.display-item.citation.isi??? ND
social impact