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<front>
<journal-meta>
<journal-id journal-id-type="publisher">WESD</journal-id>
<journal-title-group>
<journal-title>Wind Energy Science Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">WESD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Wind Energ. Sci. Discuss.</abbrev-journal-title>
</journal-title-group>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/wes-2026-193</article-id>
<title-group>
<article-title>Ten years of SCADA data from the Princess Amalia offshore wind farm: dataset description and access</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bos</surname>
<given-names>René</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kemp</surname>
<given-names>Rody</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Eneco, Rotterdam, Marten Meesweg 5, 3038 AV Rotterdam, The Netherlands</addr-line>
</aff>
<pub-date pub-type="epub">
<day>04</day>
<month>11</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>18</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 René Bos</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://wes.copernicus.org/preprints/wes-2026-193/">This article is available from https://wes.copernicus.org/preprints/wes-2026-193/</self-uri>
<self-uri xlink:href="https://wes.copernicus.org/preprints/wes-2026-193/wes-2026-193.pdf">The full text article is available as a PDF file from https://wes.copernicus.org/preprints/wes-2026-193/wes-2026-193.pdf</self-uri>
<abstract>
<p>A comprehensive set of operational data from the 120-MW Princess Amalia offshore wind farm has been made available for the scientific community to use. The dataset spans the period 2008&amp;ndash;2017 and covers meteorological, power, and control variables of all 60 turbines. This data description paper additionally contains the relevant background information of the wind farm, including coordinates, neighboring wind farms, and relevant metocean and environmental measurement campaigns. Together, these resources enable a wide range of applications, including wake model validation, wind farm control studies, operational analysis, and reliability research. The dataset is hosted by TNO and is freely available under a Creative Commons Attribution 4.0 (CC BY 4.0) license.</p>
</abstract>
<counts><page-count count="18"/></counts>
</article-meta>
</front>
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</article>