A Comprehensive Data Analysis of Electric Vehicle User Behaviors Toward Unlocking Vehicle-to-Grid Potential

Electric vehicles (EVs) improve the power grid by increasing intermittent renewable energy consumption and providing financial support to EV users via vehicle-to-grid (V2G) integration. While estimating these advantages, a number of studies have neglected consider effect driving charging behavior patterns on their results. This article provides framework that systematically evaluates behaviors charge management in light recent standards advancements. In addition, collected data habits are analyzed order provide consistent usable dataset. By evaluating individual simultaneous demand characteristics, V2G potential is further explored. Moreover, managerial recommendations for offered improving time step using Bootstrap approach more precise results than lower resolution. It also addressed use limited EVs required minimum time. According findings this study, daily travel crucial influence defining seasonal demands. continue with charging-related assessments confidence interval 95%, suggest steps ten minutes must be used. purpose study assist researchers from academia business information as they build initiatives linked infrastructure real-time account environmental aspects.