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	<title>Distributed energy resources &#8211; BIOENGINEER.ORG</title>
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		<title>Adaptive Hierarchical Learning Boosts Energy Resource Planning</title>
		<link>https://bioengineer.org/adaptive-hierarchical-learning-boosts-energy-resource-planning/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 23 Jan 2026 23:40:52 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Adaptive hierarchical learning]]></category>
		<category><![CDATA[Distributed energy resources]]></category>
		<category><![CDATA[Energy Resilience]]></category>
		<category><![CDATA[machine learning applications]]></category>
		<category><![CDATA[machine learning for energy systems]]></category>
		<category><![CDATA[renewable energy integration]]></category>
		<category><![CDATA[Uncertainty-aware planning]]></category>
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					<description><![CDATA[In the ever-evolving landscape of energy systems, the integration of distributed energy resources (DERs) poses both immense opportunities and formidable challenges. As renewable energy technologies proliferate and become increasingly decentralized, planning and managing these resources with precision have become paramount to ensuring grid reliability, efficiency, and sustainability. A groundbreaking study led by Xiang, Li, Lu, [&#8230;]]]></description>
		
		
		
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