摘要：AbstractSince adoption of the Paris Climate Agreement, efforts to reduce greenhouse gases have been conducted worldwide. Particularly in the transportation sector, researches on electric vehicles are actively underway as an effort to reduce air pollutants, and electric vehicles are expected to become a major transportation vehicle by 2030. If electric vehicles replace existing internal combustion engines, much more electricity will be required to charge the electric vehicles, which will affect the power system. To deal with this growing power demand, it is necessary to forecast and analyze the charging pattern of electric vehicles. This paper uses Bayesian inference methods with convolution to forecast the 24-hour charging pattern for electric vehicles. The results were compared with that by linear regression analysis.
