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Scalable Low-Carbon Energy System Optimization


Term:

Fall

Department:

MITEI: MIT Energy Initiative

Faculty Supervisor:

Emre Gencer

Faculty email:

egencer@mit.edu

Apply by:

09/15/2020

Contact:

Guannan He, gnhe@mit.edu

Project Description

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.

Pre-requisites

Proficiency in Python/Matlab