Leveraging the machine learning techniques for demand-side flexibility - a comprehensive review
author
Shahid, Arqum
Ahmadiahangar, Roya
Rosin, Argo
Blinov, Andrei
Korõtko, Tarmo
Vinnikov, Dmitri
statement of authorship
Arqum Shahid, Roya Ahmadiahangar, Argo Rosin, Andrei Blinov, Tarmo Korõtko, Dmitri Vinnikov
source
Electric power systems research
publisher
Elsevier
journal volume number month
vol. 238
year of publication
2025
pages
art. 111185
url
https://doi.org/10.1016/j.epsr.2024.111185
subject term
nõudlus
paindlikkus
koormus (elektrotehnika)
tehisintellekt
mikrovõrgud
keyword
demand-side flexibility
flexible loads
energy management
artificial intelligence
distributed energy resources
microgrids
ISSN
0378-7796
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/16044
https://www.scopus.com/pages/publications/85207647198?origin=resultslist
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=ELECTR%20POW%20SYST%20RES&year=2024
https://www.webofscience.com/wos/woscc/full-record/WOS:001346726200001
category (general)
Engineering
Tehnika
Energy
Energia
category (sub)
Engineering. Electrical and electronic engineering
Tehnika. Elektri- ja elektroonikatehnika
Energy. Energy engineering and power technology
Energia. Energiatehnika ja energeetika
TalTech department
elektroenergeetika ja mehhatroonika instituut
Targa linna tippkeskus
language
inglise