Robust machine-learned algorithms for efficient grid operation

Increasing penetration of variable and intermittent renewable energy resources on the energy grid poses a challenge for reliable and efficient grid operation, necessitating the development of algorithms that are robust to this uncertainty. However, standard algorithms incorporating uncertainty for g...

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Vydané v:	Environmental Data Science Ročník 4
Hlavní autori:	Christianson, Nicolas, Yeh, Christopher, Li, Tongxin, Hosseini, Mehdi, Torabi Rad, Mahdi, Golmohammadi, Azarang, Wierman, Adam
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cambridge University Press 22.04.2025
Predmet:	energy systems learning-augmented algorithms machine learning robustness online algorithms
ISSN:	2634-4602, 2634-4602
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