In the subproject B02 of the TRR391, we construct and investigate statistical methods for aggregation and decomposition to tackle the complexity of energy distribution networks, which can involve easily several 100 individual items with corresponding storage dynamics, e.g. electrical vehicles, controllable loads in households, and energy storage systems. Our analysis takes the perspective of upper-level energy transmission networks towards the statistical behavior of lower-level distribution grids at the vertical grid coupling between both layers. Aggregation of the storage dynamics of energy distribution networks can improve system operation on the transmission system via temporal couplings. Control actions decided upon on the transmission level in turn need to be mapped to the individual items composing the distribution systems. In other words, it is necessary to ensure that the action computed for aggregated abstractions can be disaggregated, i.e., control actions can be assigned in a feasible manner to the individual devices.

We thus aim to construct aggregations which admit statistical guarantees (a) on the temporal evolution of aggregated non-stationary statistics at the coupling, especially with respect to energy demand and active and reactive power fluctuations, and (b) for feasible disaggregation.