Revenue analysis of a lightweight V2G electricity trade coordinator

This paper conducts the revenue analysis of the vehicle-to- grid electricity trade broker according to the real-life energy consumption profile. The brokering scheme exploits a lightweight heuristic capable of reducing the search space by iteratively matching the time slot having the least available electricity. The total gain depends not only on how much electricity is purchased from EVs but also when it is purchased. On the winter rate, 100 EVs can sell all of their energy, while for the 200-EV case, they can sell and double the revenue on 12 out of 20 days. Next, on the summer rate, in which the peak rate interval is extended, the revenue increases by 1.5 times. At the same time, the 200-EV case sometimes brings less benefit than the 100-EV case for the given parameter set. This result indicates that the lightweight heuristic works quite efficiently, but finds a reasonable quality solution only when the number of EVs does not exceed a certain bound.