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I am a post-doctoral research associate at MIT Energy Initiative, and I have been fortunate to be supervised and funded by Professor Thomas Magnanti
The reliability of power systems under the impact of increasing renewable penetration and extreme weather conditions is a rising concern globally. My research interests include machine learning probabilistic forecasting, data-driven control and optimisation for energy systems considering uncertainty. My works aim to find appealing solutions in both system design and short-term operations. I have specific research interests in:
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Machine learning probabilistic forecasting.
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Joint chance-constrained optimization.
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Distributionally robust modelling.
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Optimal power flow analysis.
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Microgrid design and control under extreme conditions.