YoungIn (Ethan) Shin

YoungIn (Ethan) Shin is a PhD candidate whose research interests lie at the intersection of computational science and renewable energy systems. Specifically, Ethan seeks to advance fundamental knowledge of the atmospheric boundary layer (ABL) and its influence on wind farms, by developing more accurate parameterizations for turbulence in the ABL. His research leverages data assimilation and uncertainty quantifications methods to address two critical challenges in wind energy: the uncertainty in mesoscale and microscale models used for wind flow modeling and the constraints on observations needed for calibrations at the relevant locations for wind farms (~100m above Earth’s surface). A MathWorks Fellowship will support Ethan’s work to build computationally efficient, low-fidelity MATLAB models, characterizing these important environment-energy system interactions for wind farm applications such as wind farm control and wind resource assessment, and to support critical decision-making for energy systems, such as wind farm siting and design.

Ethan’s research has strong potential to further our understanding of renewable energy systems, advance global decarbonization goals, and provide tools to support future research in climate and energy research.



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