Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment-Reference-Cited by-同舟云学术

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Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment

Published:2022-12-12 Issue:3 Volume:26 Page:283-309
ISSN:1095-4244
Container-title:Wind Energy
language:en
Short-container-title:Wind Energy

Author:

Kumar Devesh¹^ORCID,Rotea Mario A.²^ORCID,Aju Emmanuvel J.²^ORCID,Jin Yaqing²

Affiliation:

1. Center for Wind Energy and Department of Electrical and Computer Engineering The University of Texas at Dallas Richardson Texas USA

2. Center for Wind Energy and Department of Mechanical Engineering The University of Texas at Dallas Richardson Texas USA

Funder

National Science Foundation

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2799

Reference37 articles.

1. Modelling and measuring flow and wind turbine wakes in large wind farms offshore

2. ChurchfieldM LeeS MoriartyP et al.A large‐eddy simulation of wind‐plant aerodynamics. In: 50th AIAA Aerospace Sciences Meeting;2012:1‐19.

3. Evaluating techniques for redirecting turbine wakes using SOWFA

4. Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization

5. Wind plant power optimization through yaw control using a parametric model for wake effects-a CFD simulation study

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1. Power output fluctuations and unsteady aerodynamic loads of a scaled wind turbine subjected to periodically oscillating wind environments;Journal of Renewable and Sustainable Energy;2024-09-01

2. Dynamic wake steering control for maximizing wind farm power based on a physics-guided neural network dynamic wake model;Physics of Fluids;2024-08-01

3. Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms;Renewable Energy;2024-05

4. Dynamic wind farm flow control using free-vortex wake models;Wind Energy Science;2024-03-26

5. Wind farm optimization by active yaw control strategy using machine learning approach;International Journal of Green Energy;2024-03-10

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