The project aims to model a smart market consisting of a single broker, which tries to minimise the difference between the
profit and loss, and tries to replicate and incubate the dynamic substance of the market.
It uses the semi-supervised technique of Reinforcement learning, to model the actor, critic and the environment.
For model creation, development and application of algorithms, and simulation, we used OpenAI Gym.
We used the public data available at Independent Electricity System Operator (IESO). IESO contains various reports
generated by the Ontario’s power grid systems, and provides detailed reports indicating the demand, supply, tariffs and all other parameters.