Zobrazeno 1 - 10
of 146
pro vyhledávání: '"AlSkaif, Tarek"'
The energy sector's digital transformation brings mutually dependent communication and energy infrastructure, tightening the relationship between the physical and the digital world. Digital twins (DT) are the key concept for this. This paper initiall
Externí odkaz:
http://arxiv.org/abs/2404.02568
This paper studies the use of conformal prediction (CP), an emerging probabilistic forecasting method, for day-ahead photovoltaic power predictions to enhance participation in electricity markets. First, machine learning models are used to construct
Externí odkaz:
http://arxiv.org/abs/2403.20149
In a decentralized household energy system comprised of various devices such as home appliances, electric vehicles, and solar panels, end-users are able to dig deeper into the system's details and further achieve energy sustainability if they are pre
Externí odkaz:
http://arxiv.org/abs/2208.10265
Autor:
Santos, Leticia de Oliveira, AlSkaif, Tarek, Barroso, Giovanni Cordeiro, Carvalho, Paulo Cesar Marques de
Publikováno v:
In Solar Energy December 2024 284
Publikováno v:
In Energy Reports December 2024 12:3830-3842
While the potential for peer-to-peer electricity trading, where households trade surplus electricity with peers in a local energy market, is rapidly growing, the drivers of participation in this trading scheme have been understudied so far. In partic
Externí odkaz:
http://arxiv.org/abs/2109.02452
Autor:
Birkeland, Dane, AlSkaif, Tarek
Publikováno v:
In Sustainable Energy, Grids and Networks June 2024 38
In a decentralized household energy system consisting of various devices such as washing machines, heat pumps, and solar panels, understanding the electric energy consumption and production data at the granularity of the device helps end-users be clo
Externí odkaz:
http://arxiv.org/abs/2108.01504
With the inclusion of smart meters, electricity load consumption data can be fetched for individual consumer buildings at high temporal resolutions. Availability of such data has made it possible to study daily load demand profiles of the households.
Externí odkaz:
http://arxiv.org/abs/2108.01433
The availability of residential electric demand profiles data, enabled by the large-scale deployment of smart metering infrastructure, has made it possible to perform more accurate analysis of electricity consumption patterns. This paper analyses the
Externí odkaz:
http://arxiv.org/abs/2105.08537