Fraunhofer-Institut für System- und Innovationsforschung ISI

Filters
Reset filters

Settings
Now showing 1 - 2 of 2
  • Publication
    Plug-in electric vehicles' automated charging control: iZEUS Project
    ( 2017)
    Dallinger, David
    ;
    Kohrs, Robert
    ;
    Mierau, Michael
    ;
    Marwitz, Simon
    ;
    Wesche, Julius P.
    This chapter examines how plug-in electric vehicles can be managed to balance the fluctuation of renewable electricity sources. The evaluations of this chapter were object of the iZEUS Project ""Intelligent Zero Emission Urban System"" funded by the German Federal Minister for Economic Affairs and Energy. In this context, different control strategies are introduced and, in order to investigate indirect control via electricity tariffs, an electricity market analysis of a system with a high share of generation from renewable electricity sources has been conducted. The analysis uses driving data collected from battery electric and plug-in hybrid vehicles in a research project which means that real charging and driving behavior can be considered. The results show that it is difficult to implement smart charging based on economic arguments because the incentives from day-ahead electricity markets are relatively small. In addition, a novel, autonomous control approach is being discussed for plug-in electric vehicles. While measuring the voltage at the grid connection point, plug-in electric vehicles are able to fully independently generate operation schedules that can avoid load peaks and integrate fluctuating power outputs from distributed renewable generation sources. The results reveal that combining indirect, price-based control to consider the system level with autonomous voltage-based control to consider the situation in distribution grids is a very promising control approach that allows electric vehicles to benefit from sustainable renewable generation and avoids load peaks due to simultaneous charging.
  • Publication
    Smart grid agent: Plug-in electric vehicle
    ( 2014)
    Dallinger, David
    ;
    Link, Jochen
    ;
    Büttner, Markus
    This study describes a method for programming a plug-in electric vehicle (PEV) agent that can be used in power system models and in embedded systems implemented in real PEVs. Implementing the software in real-life applications and in simulation tools enables research with a high degree of detail and practical relevance. Agent-based programming, therefore, is an important tool for investigating the future power system. To demonstrate the PEV agent behavior, an optimization algorithm is presented and two battery aging methods, as well as their effect on vehicle-to-grid operation, are analyzed. Aging costs based on the depth-of-discharge result in shallow cycles and a strong dependency on driving behavior, because the state-of-charge affects the discharging process. In contrast, aging costs based on energy throughput calculations result in deeper cycles and V2G operation, which is less dependent on driving behavior.