Modelling of turbine power and local wind conditions in wind farm using an autoencoder neural network

^*Corresponding author for this work

Research output: Contribution to conference › Conference abstract for conference › Research

Original language	English
Publication date	2022
Number of pages	3
Publication status	Published - 2022
Event	The Science of Making Torque from Wind 2022 - Delft, Netherlands Duration: 1 Jun 2022 → 3 Jun 2022 Conference number: 9 https://www.torque2022.eu/

Conference	The Science of Making Torque from Wind 2022
Number	9
Country/Territory	Netherlands
City	Delft
Period	01/06/2022 → 03/06/2022
Internet address	https://www.torque2022.eu/

Keywords

@conference{c291fef80a8840309f8bf42b8f3b0f46,

title = "Modelling of turbine power and local wind conditions in wind farm using an autoencoder neural network",

keywords = "Wind farm, Wake effects, Wake sources, Surrogate models, Artificial neural network, Auto-encoder, Latent variables, Parametrization",

author = "Suguang Dou and Nikolay Dimitrov",

year = "2022",

language = "English",

note = "The Science of Making Torque from Wind 2022, Torque 2022 ; Conference date: 01-06-2022 Through 03-06-2022",

url = "https://www.torque2022.eu/",

}

TY - ABST

T1 - Modelling of turbine power and local wind conditions in wind farm using an autoencoder neural network

AU - Dou, Suguang

AU - Dimitrov, Nikolay

N1 - Conference code: 9

PY - 2022

Y1 - 2022

KW - Wind farm

KW - Wake effects

KW - Wake sources

KW - Surrogate models

KW - Artificial neural network

KW - Auto-encoder

KW - Latent variables

KW - Parametrization

M3 - Conference abstract for conference

T2 - The Science of Making Torque from Wind 2022

Y2 - 1 June 2022 through 3 June 2022

ER -