Model-Based Quantification of Load Shift Potentials and Optimized Charging of Electric Vehicles

Hahn, Tobias and Schönfelder, Martin and Jochem, Patrick and Heuveline, Vincent and Fichtner, Wolf (2013): Model-Based Quantification of Load Shift Potentials and Optimized Charging of Electric Vehicles. Published in: Smart Grid and Renewable Energy , Vol. 4, (2013): pp. 398-408.

Abstract

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Electric Mobility; Load Shifting; Charging Management; Optimization
• Subjects: O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R4 - Transportation Economics > R42 - Government and Private Investment Analysis ; Road Maintenance ; Transportation Planning

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