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Collective wind farm operation based on a predictive model increases utility-scale energy production

Howland, Michael F. and Bas Quesada, Jesús and Pena Martínez, Juan José and Palou Larrañaga, Felipe and Yadav, Neeraj and Chawla, Jasvipul S. and Sivaram, Varun and Dabiri, John O. (2022) Collective wind farm operation based on a predictive model increases utility-scale energy production. . (Unpublished)

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Wind turbines located in wind farms are operated to maximize only their own power production. Individual operation results in wake losses that reduce farm energy. In this study, we operate a wind turbine array collectively to maximize total array production through wake steering. The selection of the farm control strategy relies on the optimization of computationally efficient flow models. We develop a physics-based, data-assisted flow control model to predict the optimal control strategy. In contrast to previous studies, we first design and implement a multi-month field experiment at a utility-scale wind farm to validate the model over a range of control strategies, most of which are suboptimal. The flow control model is able to predict the optimal yaw misalignment angles for the array within +/-5 degrees for most wind directions (11-32% power gains). Using the validated model, we design a control protocol which increases the energy production of the farm in a second multi-month experiment by 2.7% and 1.0%, for the wind directions of interest and for wind speeds between 6 and 8 m/s and all wind speeds, respectively. The developed and validated predictive model can enable a wider adoption of collective wind farm operation.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemJournal Article
Howland, Michael F.0000-0002-2878-3874
Pena Martínez, Juan José0000-0001-9395-7976
Yadav, Neeraj0000-0002-1806-119X
Chawla, Jasvipul S.0000-0002-9129-7975
Sivaram, Varun0000-0002-0878-6349
Dabiri, John O.0000-0002-6722-9008
Additional Information:Attribution 4.0 International.
Record Number:CaltechAUTHORS:20220207-90072000
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113313
Deposited By: George Porter
Deposited On:08 Feb 2022 16:39
Last Modified:25 Aug 2022 14:37

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