A simulation environment for smart charging of electric vehicles using a multi-objective evolutionary algorithm

Abstract

Integration of the electric vehicles (EV) into the power grid is one of the most important efforts to reduce CO2 emissions in the transport sector. Electric vehicles can put significant stress on sections of the distribution grid while charging. In order to maintain grid availability, it is essential that the individual charging schedules are aligned with each other such that the total load does not exceed the grid's maximum capacity. In addition to this hard constraint, user preferences, constraints enforced by the battery, other grid loads, market prices, consumer tariffs, and possibly other factors have to be considered when creating charging schedules. In this paper, we present the design of a simulation environment, which produces charging schedules using a multi-objective, evolutionary optimization algorithm. © 2011 Springer-Verlag.