Retrospective de‐trending of wind site turbulence using machine learning-Reference-Cited by-同舟云学术

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Retrospective de‐trending of wind site turbulence using machine learning

Published:2022-02-17 Issue:7 Volume:25 Page:1173-1187
ISSN:1095-4244
Container-title:Wind Energy
language:en
Short-container-title:Wind Energy

Author:

Tough Fraser¹²,Hart Edward³^ORCID

Affiliation:

1. Renewable Energy Systems (RES) Ltd. Kings Langley UK

2. School of Mathematics and Statistics University of Glasgow University Place Glasgow UK

3. Wind Energy and Control Centre, Department of Electronic and Electrical Engineering University of Strathclyde Glasgow UK

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2720

Reference23 articles.

1. Sustainable decommissioning of an offshore wind farm

2. Lifetime extension of onshore wind turbines: A review covering Germany, Spain, Denmark, and the UK

3. Offshore wind farm repowering optimization

4. Observed Characteristics of the Atmospheric Boundary Layer

5. Observations of a multi-level turbulence structure in a very stable atmospheric boundary layer

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