  Spatially highly-resolved capacity expansion models are often simplified to a
lower spatial resolution because they are computationally intensive. The
simplification mixes sites with different renewable features while ignoring
transmission lines that can cause congestion. As a consequence, the results may
represent an infeasible system when the capacities are fed back at higher
spatial detail. Thus far there has been no detailed investigation of how to
disaggregate results and whether the spatially highly-resolved disaggregated
model is feasible. This is challenging since there is no unique way to invert
the clustering.
  This article is split into two parts to tackle these challenges. First,
methods to disaggregate spatially low-resolved results are presented: (a) an
uniform distribution of regional results across its original highly-resolved
regions, (b) a re-optimisation for each region separately, (c) an approach that
minimises the "excess electricity". Second, the resulting highly-resolved
models' feasibility is investigated by running an operational dispatch. While
re-optimising yields the best results, the third inverse method provides
comparable results for less computational effort. Feasibility-wise, the study
design strengthens that modelling countries by single regions is insufficient.
State-of-the-art reduced models with 100-200 regions for Europe still yield
3%-7% of load-shedding, depending on model resolution and inverse method.
