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<a href=/tags/energy-markets/index.xml title=RSS aria-label=RSS><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentcolor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" height="23"><path d="M4 11a9 9 0 019 9"/><path d="M4 4a16 16 0 0116 16"/><circle cx="5" cy="19" r="1"/></svg></a></h1></header><article class="post-entry tag-entry"><header class=entry-header><h2>Transfer learning applies to energy market bidding</h2></header><div class=entry-content><p>An interesting approach to bidding of energy storage assets, showing that training on New York data is transferable to Queensland.</p></div><footer class=entry-footer><span title='2023-12-14 00:15:00 +0000 UTC'>December 14, 2023</span></footer><a class=entry-link aria-label="post link to Transfer learning applies to energy market bidding" href=https://yanirseroussi.com/til/2023/12/14/transfer-learning-applies-to-energy-market-bidding/></a></article></main><footer class=footer><span>Text and figures licensed under <a href=https://creativecommons.org/licenses/by-nc-nd/4.0/ target=_blank rel=noopener>CC BY-NC-ND 4.0</a> by <a href=https://yanirseroussi.com/about/>Yanir Seroussi</a>, except where noted otherwise |</span> | ||
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