Abstract
Abstract This paper presents an electric vehicle (EV) optimization scheduling method that incorporates vehicle-to-grid (V2G) responses within the framework of a carbon market. Initially, the method characterizes the grid-connected and off-grid operational states of EVs. These states are represented by three types of probability density functions derived from historical data. Subsequently, a V2G response model is formulated based on consumer psychology theory. The approach then integrates the impact of carbon trading on the charging and discharging schedules of EVs, aiming to minimize carbon trading costs. The resulting optimization scheduling model is solved using the CPLEX solver.
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