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...

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Vydané v:	Applied energy Ročník 304; s. 117733
Hlavní autori:	Touzani, Samir, Prakash, Anand Krishnan, Wang, Zhe, Agarwal, Shreya, Pritoni, Marco, Kiran, Mariam, Brown, Richard, Granderson, Jessica
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Ltd 15.12.2021 Elsevier
Predmet:	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
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