Using Principal Component Analysis (PCA), the nodal injection and line flow
patterns in a network model of a future highly renewable European electricity
system are investigated. It is shown that the number of principal components
needed to describe 95% of the nodal power injection variance first increases
with the spatial resolution of the system representation. The number of
relevant components then saturates at around 76 components for network sizes
larger than 512 nodes, which can be related to the correlation length of wind
patterns over Europe. Remarkably, the application of PCA to the transmission
line power flow statistics shows that irrespective of the spatial scale of the
system representation a very low number of only 8 principal flow patterns is
sufficient to capture 95% of the corresponding spatio-temporal variance.
This result can be theoretically explained by a particular alignment of some
principal injection patterns with topological patterns inherent to the network
structure of the European transmission system
