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  • Presentation | NH51B: Data Science for Weather and Climate Extremes: Risks, Drivers, and Impacts III Oral
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  • NH51B-07: Vulnerability of U.S. Power Generation to Extreme Weather: A Data-Driven Analysis
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Author(s):
Yi Lu, Stanford University (First Author, Presenting Author)
Tao Sun, Stanford University
Ram Rajagopal, Stanford University


Extreme weather—like hurricanes, snowstorms, and heat waves—can seriously affect the ability of power plants to produce electricity. In this study, we examine how various types of power generation across the United States, including wind, solar, natural gas, coal, and other sources, are affected during such extreme weather events. We integrate government-reported energy data with computer-based simulations to understand how much energy was expected versus what was actually produced. For example, hurricanes, blizzards led to major shortfalls in wind power generation. Our results show that many power sources are vulnerable to extreme weather, and that better forecasting and preparation can help prevent power outages in the future. This work can help grid operators and decision-makers plan for a more reliable and climate-resilient energy system.



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