*2.4. Simplifications Aimed to Find General Trends Rather than Route-Specific Results*

There are some costs which vary only in steps, and these steps can make it difficult to see the general trend in the costs. For example, when the headway is varied, the number of buses needed for a route changes in steps of one. The exact headway at which the number of buses changes is not necessarily the same for the compared charging strategies. Comparing two types of buses, it may sometimes look as if one is more cost effective than the other, but with just a slight adjustment of the

headway, the result can be the opposite. To avoid this, the cost model is defined to calculate as if it is possible to buy a non-integer number of buses, and by extension, a non-integer number of depot chargers. Normally several routes are driven by the same operator, and then the possibility to use a non-integer number of buses for a route is even more reasonable since buses and drivers can be shared between different routes, making it possible to plan the bus schedules so that buses can operate on several routes.

The number of end-stop chargers are, however, an integer in the model, as the step in the number of chargers will be much more important for the cost effectiveness of the different charging strategies. End-stop chargers are sometimes less well-utilized than depot chargers, and it is important that the model includes that effect, as it is a reason why the TCO for end-stop charging significantly varies between different routes. Furthermore, end-stop chargers can only support the routes that use the bus stop at which they are placed and can therefore not be shared as easily between routes as the buses can.

When planning bus schedules for a route, there is often a need for buses to be inactive and wait for the next departure. The need for such waiting time can vary in a very random way with changes in route properties and timetables. To avoid such "noise" influences on the TCO calculations, the TCO model does not create real bus schedules. Instead, the model just estimates the total number of buses needed in traffic, how many will be driving to and from the depot, and how many will be charging at different times during the day. This simplification is a feature and not a bug, since it allows for a clearer illustration of the system effects when analysing the total amount of buses occupied by different tasks rather than focusing on analysing the buses individually.

Another simplification is that the model does not keep track of the State of Charge (SoC) of individual batteries, but instead, the SoC of the buses are ensured by a few conditions regarding the size of the required batteries, and by determining how much charging is required in total to achieve energy balance of the fleet over the day. To allow for this simplification, the model assumes that the batteries are sized to handle some worst-case energy use that individual buses can experience between charges. Optimizing the battery size can further reduce costs, but this is not included in this version of the cost model.
