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Scalable Low-Carbon Energy System Optimization
MITEI: MIT Energy Initiative
Guannan He, firstname.lastname@example.org
Climate change mitigation is contingent on identifying pathways for the deep decarbonization of the energy sector, calling for powerful energy system optimization tools. The modelling capability of energy system optimization models is currently limited due to computational intractability resulting from the spatiotemporal complexities of the problem and the use of integer variables to characterize operational flexibility of certain technologies. This project will investigate numerical methods and domain-reduction techniques to solve challenging combinatory optimization problems for low-carbon energy systems. Students will get research experiences and knowledge in the combined area of machine learning and low-carbon energy systems.
Proficiency in Python/Matlab