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Scheduling algorithms for Smart Charing of Adaptive Electric Vehicles (EVs)

Primary supervisor

Adel Nadjaran Toosi

In recent years, the production and sales of Electric Vehicles (EVs) have been known as an important growth worldwide. This evolution is mainly due to the severe limits regarding greenhouse gas emission that cannot be respected by internal combustion vehicles. The expected growth in EV adoption creates large opportunities for grid integration, through flexible smart charging and vehicle to grid (V2G) or vehicle to premises (V2P) to moderate peak demand.

Student cohort

Double Semester


In this project, we will look into the development of scheduling algorithms and software systems that enables EVs to participate in the grid demand response programs by either returning electricity to the grid/premise or by throttling their charging rate. 


Required knowledge

Cloud computing and distributed systems knowledge

Python/Java programming skills

Be familiar with optimization techniques