Managing the charging process of a large number of electric vehicles to decrease the pressure on the local electricity grid is of high interest to the utilities. Using efficient mathematical optimization techniques, t...Managing the charging process of a large number of electric vehicles to decrease the pressure on the local electricity grid is of high interest to the utilities. Using efficient mathematical optimization techniques, the charging behavior of electric vehicles shall be optimally controlled taking into account network, vehicle, and customer requirements. We developed an efficient algorithm for calculating load shift potentials defined as the range of all charging curves meeting the customer’s requirements and respecting all individual charging and discharging constraints over time. In addition, we formulated a mixed integer linear program (MIP) applying semi-continuous variables to find cost-optimal load curves for every vehicle participating in a load shift. This problem can be solved by e.g. branch-and-bound algorithms. Results of two scenarios of Germany in 2015 and 2030 based on mobility studies show that the load shifting potential of EV is significant and contribute to a necessary relaxation of the future grid. The maximum charging and discharging power and the average battery capacity are crucial to the overall load shift potential.展开更多
基金supported by the Energy Solution Center(EnSoC),an association of major industrial corporations and research institutions in Germanysupport by Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of Karlsruhe Institute of Technology
文摘Managing the charging process of a large number of electric vehicles to decrease the pressure on the local electricity grid is of high interest to the utilities. Using efficient mathematical optimization techniques, the charging behavior of electric vehicles shall be optimally controlled taking into account network, vehicle, and customer requirements. We developed an efficient algorithm for calculating load shift potentials defined as the range of all charging curves meeting the customer’s requirements and respecting all individual charging and discharging constraints over time. In addition, we formulated a mixed integer linear program (MIP) applying semi-continuous variables to find cost-optimal load curves for every vehicle participating in a load shift. This problem can be solved by e.g. branch-and-bound algorithms. Results of two scenarios of Germany in 2015 and 2030 based on mobility studies show that the load shifting potential of EV is significant and contribute to a necessary relaxation of the future grid. The maximum charging and discharging power and the average battery capacity are crucial to the overall load shift potential.
