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		<title>Efficient Tail Risk Assessment for Power Systems</title>
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		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 05 Jan 2026 07:54:27 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[computational framework for risk evaluation]]></category>
		<category><![CDATA[efficiency in power system simulations]]></category>
		<category><![CDATA[extreme events in power grids]]></category>
		<category><![CDATA[probabilistic modeling for utility operators]]></category>
		<category><![CDATA[tail risk assessment in power systems]]></category>
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					<description><![CDATA[In an era where the reliability and stability of power systems underpin the very fabric of modern society, the capacity to accurately assess risks associated with system overloading is not just desirable—it is essential. Recent research spearheaded by Tan, Ye, Zhao, and colleagues introduces a groundbreaking computational framework designed specifically to tackle the immense challenges [&#8230;]]]></description>
		
		
		
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