A New Dynamical Bottom-Up Energy Model for Germany

The results of calculations made by bottom-up linear optimization models (LP) are to some extent determined by the applied optimization strategy. Existing energy system models most commonly employ an optimization strategy which are known as perfect-foresight, i.e. an optimization of the total time period in one system of equations. Perfect foresight means that the model in principle would “know” all the future parameters or boundary conditions and therefore could react on future exogenously given changes in advance of these changes taken place (e.g. prices of energy carriers, climate gas reduction policy etc.) The new IKARUS-Model described is a time-step or myopic dynamical bottom-up linear optimization model where each time interval is optimized by itself taking into account the heritage due to results from all periods before. So the model does not take into account future changes in each time-step optimization. It is therefore a model with a more realistic character of prognosis and projection. For example with this model aspects like reaction on sudden changes, flexibility of technical scenarios, lost opportunities etc. can be examined. In addition – assuming sufficiently short time-step intervals – interaction with macroeconomic input-output models or dependencies on elasticities, technological learning, economy of scale etc. as well as other non-linear (dynamical) effects can be taken into account without an iterative optimization process. Recent calculations with this model for Germany up to 2030 show that consistent, reasonable and plausible future energy scenarios can be produced and analyzed. Furthermore some exemplary calculations of lost opportunities and (in)flexibility of technological scenarios to unexpected sudden changes are shown. Future work will include an endogenous integration of non-linear effects and a more detailed vintage capacity calculation, both being components of an integrated dynamical recursive model structure.