Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these r...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Applied energy Ročník 304; s. 117733
Hlavní autoři:	Touzani, Samir, Prakash, Anand Krishnan, Wang, Zhe, Agarwal, Shreya, Pritoni, Marco, Kiran, Mariam, Brown, Richard, Granderson, Jessica
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Ltd 15.12.2021 Elsevier
Témata:	algorithms batteries carbon Control systems Deep deterministic policy gradient algorithm Deep reinforcement learning Distributed energy resources Energy efficiency industry issues and policy Load flexibility POWER TRANSMISSION AND DISTRIBUTION Smart buildings Deep deterministic policy gradient algorithm Smart buildings Distributed energy resources Load flexibility Deep reinforcement learning Control systems Energy efficiency
ISSN:	0306-2619, 1872-9118
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!