A data-driven machine learning approach for yaw control applications of wind farms

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	100471
Journal	Theoretical and Applied Mechanics Letters
Volume	13
Issue number	5
State	Published - 2023

Cite this

@article{3efd35dfd5394c728869eac978cefae5,

title = "A data-driven machine learning approach for yaw control applications of wind farms",

author = "Christian Santoni and Zexia Zhang and Fotis Sotiropoulos and Ali Khosronejad and Christian Santoni-Ortiz",

year = "2023",

language = "English",

volume = "13",

pages = "100471",

journal = "Theoretical and Applied Mechanics Letters",

number = "5",

}

TY - JOUR

T1 - A data-driven machine learning approach for yaw control applications of wind farms

AU - Santoni, Christian

AU - Zhang, Zexia

AU - Sotiropoulos, Fotis

AU - Khosronejad, Ali

AU - Santoni-Ortiz, Christian

PY - 2023

Y1 - 2023

M3 - Article

VL - 13

SP - 100471

JO - Theoretical and Applied Mechanics Letters

JF - Theoretical and Applied Mechanics Letters

IS - 5

ER -