Insights in wind field reconstruction from two nacelles' LiDAR in the same offshore wind farm

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

The global rise in offshore wind farms underscores the need to cut costs and optimise energy production. As turbines increase in size and wind farms become more concentrated, mitigating downstream wake effects is crucial for operational efficiency. LiDAR technology, offering advantages like eliminating the need for meteorology masts, has been extensively discussed in the literature. However, it indirectly measures wind parameters, relying on assumptions and embedded algorithms. Wind field reconstruction (WFR) methods empower users with more control over LiDAR measurements, allowing tailored flow assumptions and parameter estimation. Using LiDAR data from two sequential campaigns at a wind farm, our research analyses LiDAR performance validated with SCADA measurements and applies WFR for wind field parameters estimation. Comparative analyses of wind parameters from different sources, particularly downstream turbines, demonstrate the robustness of WFR. The reconstructed wind field is compared with SCADA data for a comprehensive assessment.

Original languageEnglish
Title of host publicationJournal of Physics: Conference Series
PublisherIOP Publishing
Pages012014
Number of pages10
Volume2875
Edition1
DOIs
Publication statusPublished - 2024
EventEERA DeepWind Conference 2024 - Norway, Trondheim
Duration: 17 Jan 2024 → …
https://www.deepwind.no/

Publication series

NameJournal of Physics: Conference Series
ISSN (Print)1742-6588

Conference

ConferenceEERA DeepWind Conference 2024
CityTrondheim
Period17/01/24 → …
Internet address

Bibliographical note

Funding Information:
This research was supported by funding from the MaDurOS program from VLAIO (Flemish Agency for Innovation and Entrepreneurship) and SIM (Strategic Initiative Materials) through project SBO SEAFD and the intercluster SIM-Blue Cluster ICON Rainbow. The authors, moreover, acknowledge the support via the Flemish Government under the \u201COnderzoeksprogramma Artifici\u00EBle Intelligentie (AI) Vlaanderen\u201D program.

Publisher Copyright:
© 2024 Institute of Physics Publishing. All rights reserved.

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