Abstract
As a result of increase in the introduction of Renewable Energy (RE) such as solar power generation and wind power generation, the surplus problem of RE at off-peak electric power load actually occurs and then the output of RE is being curtailed. Regarding preventing global warming, it is desirable to reduce the amount of RE output curtailment as much as possible and many studies have been carried out to tackle this issue in order to make the best use of RE. In this paper, valley-filling optimization problem is applied to V2G daily planning because EVs are expected to spread in the future. In the application, the target generation is set and the generation after RE curtailment is moved as close to the target generation as possible through V2G charging and discharging. Since there are uncertainties regarding the available time and available amount of EV battery, this paper proposes a stochastic valley-filling approach which deals with the uncertainties to solve the problem. This paper also conducts simulation on the day when the RE output was actually curtailed and evaluates the reduced amount of the RE output curtailment by V2G.
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