As part of the project Dynamis the Forschungsstelle für Energiewirtschaft develops a model of the German energy system which couples its energy supply optimisation models ISAaR and MInGa with four energy application submodels for the industry sector, the commerce, trade and service sector, private households and the transport sector. In this course the target is not to simply analyze scenarios but to evaluate measures to reduce CO2 emissions in the context of the dynamic changing system.
In order to model the whole energy system in a dynamic way which is not dependent on scenarios, one has to exactly define the program sequences as well as the interfaces between the submodels. The main output of the energy application submodels is the time-resolved energy demand for each energy source as well as the emissions and measure related costs within the sector. This information will be passed to the optimisation models which simulate the supply and therefore the energy source related emissions and costs.
In terms of the energy application sectors and especially the transport sector there are three main issues to address in order to correctly depict the functional relations and the impact of applied CO2 abatement measures: the translation of the measure input, the displacement effect resulting from it and the arising costs and emissions. Applied reduction measures can either impact the development of the composition, the usage and therefore the energy demand as well as the time of the energy demand of the fleet. The implementation of a measure has a direct relation to the displacement effects which represent the change in comparison to the natural replacement like e.g. the purchase of a new car to exchange an old one. The natural replacement is defined by a reference. The costs and the emissions in one sector are also compared to the reference.
The method allows to analyse different measures in different scales and for different years very easily. The figure shows the results in terms of change in CO2 emissions per technology and cumulative for an example measure. In this case, the measure is an extra investment of 30 billion Euros in battery electric vehicles in the time between 2021 and 2030.
Figure: Change of CO2 emissions by energy source of cars and cumulative CO2 reduction after applying the measure of 30 billion Euros for electrical cars
A more detailed set of results including consequential effects that are caused by the measure but become effective in the years after 2030 will be presented in the paper. Besides changes of the car fleet composition itself, also differences in the fleet specific values such as the average fuel consumption of conventional cars are evaluated. In this context the paper presents results concerning the effects of applied measures on the fleet’s age structure.
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