A Charging Management of Electric Vehicles Based on Campus Survey Data

Abstract

Road transport electrification has a great potential to reduce greenhouse gas emissions and oil consumptions. However, massive integration of electric vehicles (EVs) may cause a trouble on power grid. This point of view looks at the future state of EV development, charging scheduling and drivers' behaviors are becoming increasingly important to charging management strategy. An optimal charging management leads to minimum effects on power grid, reducing peak power via vehicle to grid (V2G) mode and lower charging costs. In order to make an optimum charging management strategy, it requires some information of driver behavior, such as daily driving, parking times and usage frequency of the vehicle. At this perspective, a campus based driver behavior is gathered with face to face survey in Yildiz Technical University, Turkey. Survey data is utilized to determine daily optimum charging profile and increase the functionality of EVs. In this study, the comparison of possible effects of different charging scenarios on power grid are presented and analyzed. A case study is performed in the university campus and the simulation is realized in MATLAB/Simulink environment with actual data.