3.1.5. Controller Strategies

In order to quantify the impact of different controller strategies or user preferences on the flexibility potential of electric vehicles, we implemented two controller strategies.

The first controller strategy is to charge the vehicle at minimal costs but as soon as possible. Such behavior can be simulated by adding a minimal price increment onto the electricity prices (see Equation (18)).

$$c\_t^{\text{im/ex}} = c\_t^{\text{grid, im/ex}} + c\_t^{\text{contr}} \qquad \qquad \forall t \in [1, T] \tag{18}$$

*c* grid, im/ex *<sup>t</sup>* denotes the actual electricity prices/revenues and *<sup>c</sup>*contr *<sup>t</sup>* the term that is added in accordance with the controller strategy. In the case of the first controller strategy, minimal price increments are added in the range of 0.00001 to 0.00002 \$/kWh and therefore do not affect the actual price of electricity for the user. In the case of constant electricity prices, the optimizer would choose the first possible time steps in order to charge at minimal costs. For the rest of this publication, this operating strategy is denoted as "+*MI*".

In order to conserve battery life, a second controller strategy is to charge the vehicle as late as possible and therefore to keep the SoC of the EV battery as low as possible as long as possible. This controller strategy can be implemented either by the addition of a minimal price decrement in Equation (18) or in the optimizer by default. In our case, this behavior was implemented by default in the solver. Therefore, this controller strategy is not separately labeled.

Table 4 lists the five simulated operating strategies that represent the combination of the three electricity tariffs and the two controller strategies.


**Table 4.** Simulated operating strategies that represent the combination of electricity tariffs and controller strategies.
