Samenvatting
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.
Originele taal-2 | English |
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Titel | Journal of Physics: Conference Series |
Uitgeverij | IOP Publishing |
Pagina's | 012014 |
Aantal pagina's | 10 |
Volume | 2875 |
Uitgave | 1 |
DOI's | |
Status | Published - 2024 |
Evenement | EERA DeepWind Conference 2024 - Norway, Trondheim Duur: 17 jan 2024 → … https://www.deepwind.no/ |
Publicatie series
Naam | Journal of Physics: Conference Series |
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ISSN van geprinte versie | 1742-6588 |
Conference
Conference | EERA DeepWind Conference 2024 |
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Stad | Trondheim |
Periode | 17/01/24 → … |
Internet adres |
Bibliografische nota
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