Data-driven Modelling of Wind Farm Flow Control Strategies - Hardcover

Cassamo, Nassir; Van Wingerden, Jan-Willem

Hardcover

ISBN 10: 3031841158 ISBN 13: 9783031841156

Publisher: Springer, 2025

Synopsis

This book presents data-driven algorithms used in the context of wind farm modelling and exploits their relation with concepts from non-linear dynamical system theory. The algortihms include Input Output Dynamic Mode Decomposition and their combination with the Koopman Operator theory. The latter improves on modelling and analysis of the aerodynamic interaction between wind turbines in wind farms and assists in uncovering insights into the existing dynamics and improves models accuracy. The authors introduce the topic of wind farm flow control, illustrating current strategies devised to overcome power losses in wind plants due to the aerodynamic interaction between turbines. Although controlling wind farms as a whole is becoming increasingly important, the high dimensions and governing non-linear dynamics inherent of wind farm systems make the design of numerical optimal controllers computationally expensive. This book describes a possible pathway to circumvent this challenge through reduced order models that can embed the existing non-linearities. The authors make use of high fidelity open-source simulation datasets and developed algorithms to fully show the potential of this approach using visual results. The reader is motivated to use the datasets and algorithms and exploit the potential of the reduced order models.

About this title

About the Author

Nassir Cassamo is a Senior Engineer at Vattenfall in Amsterdam, The Netherlands, working in the field of Wind Farm and Hybrid Power Plant Control and Optimisation. He has previosuly worked as a researcher in The Netherlands Organisation for Applied Scientific Research (TNO) in the field of Wind Farm Flow Control. He holds a BSc. and an MSc. degree in Mechanical Engineering from Insituto Superior Técnico, specializing in Systems and Control Engineering, in 2018 and 2020, respectively. 

Jan-Willem van Wingerden is a Full Professor at the Delft University of Technology, Delft Center for Systems and Control (DCSC), in Delft, The Netherlands. He received his M.Sc. and Ph.D., both cum laude from the Delft University of Technology, Delft, The Netherlands, in 2004 and 2008, respectively. His current research focuses on the control of wind energy systems and data-driven control.

From the Back Cover

This book presents data-driven algorithms used in the context of wind farm modelling and exploits their relation with concepts from non-linear dynamical system theory. The algortihms include Input Output Dynamic Mode Decomposition and their combination with the Koopman Operator theory. The latter improves on modelling and analysis of the aerodynamic interaction between wind turbines in wind farms and assists in uncovering insights into the existing dynamics and improves models accuracy. The authors introduce the topic of wind farm flow control, illustrating current strategies devised to overcome power losses in wind plants due to the aerodynamic interaction between turbines. Although controlling wind farms as a whole is becoming increasingly important, the high dimensions and governing non-linear dynamics inherent of wind farm systems make the design of numerical optimal controllers computationally expensive. This book describes a possible pathway to circumvent this challenge through reduced order models that can embed the existing non-linearities. The authors make use of high fidelity open-source simulation datasets and developed algorithms to fully show the potential of this approach using visual results. The reader is motivated to use the datasets and algorithms and exploit the potential of the reduced order models.

• Provides a thorough review of wind farm control strategies.
• Illustrates wind farm control strategies with data from simulations and using reduced order models.
• Maximizes reader understanding of state of the art data-driven algorithms applied to wind farm control.

Edition details

• Publisher: Springer
• Publication date: 2025
• Language: English
• ISBN 10: 3031841158
• ISBN 13: 9783031841156
• Binding: Hardcover
• Number of pages: 170