A Win-Win Algorithm for Learning the Flexibility of Aggregated Residential Appliances
In the Demand Side Management (DSM) context, residential customers have the potential for reducing costs and relieving the grid with non-thermostatic appliances. These appliances might be optimally scheduled by a central entity, taking into account user preferences. However, the user might not be ab...
Guardado en:
Autores principales: | Claudia De Vizia, Edoardo Patti, Enrico Macii, Lorenzo Bottaccioli |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/6505e0e70dab42aa973e8214a9f6020f |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Exploring an Efficient POI Recommendation Model Based on User Characteristics and Spatial-Temporal Factors
por: Chonghuan Xu, et al.
Publicado: (2021) -
Appliance Level Energy Characterization of Residential Electricity Demand: Prospects, Challenges and Recommendations
por: Rehan Liaqat, et al.
Publicado: (2021) -
The New Face of Internet User Typology: The Case of Thailand
por: Krairit,Donyaprueth
Publicado: (2018) -
When usage matters: time-of-use analysis of Cape Town's Day Zero drought response
por: M. J. Booysen, et al.
Publicado: (2021) -
Financial and operational sustainability of a gravity-fed rural piped water supply system in Malawi
por: Patrick Mwagomba, et al.
Publicado: (2021)