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avkhimen / repository
This project implements Q-Learning to find the optimal policy for charging and discharging electric vehicles in a V2G scheme under conditions of uncertain commitment of EV owners. The problem is modelled as a multi-objective multi-agent cooperative game. Project is part of fulfillment criteria for ECE 730 course at the University of Alberta.
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To run the simulation make sure the AESO_2020_demand_price.csv file is in the same directory as the simulation.py file.
See the report here.
To run use:
python simulation.py --n --id_run --pen --scale
stats_output_with_v2g.py and stats_output_no_v2g.py are used to generate statistics after the model has been trained.
Requrements: