  In this article, we investigate mismatch of renewable electricity production
to demand and how this is affected by flexibility options on the supply side.
We assess the impact of spatial and temporal smoothing on reliability of
production and whether they can reduce risks of variation. As a case study we
pick a simplified (partial) representation of the Norwegian electricity system
and focus on wind power. We represent regional electricity production and
demand through two stochastic processes: the wind capacity factors are modelled
as a two-dimensional Ornstein-Uhlenbeck process and electricity demand consists
of realistic base load and temperature-induced load coming from a
deseasonalised autoregressive process. We validate these processes, that we
have trained on historical data, through Monte Carlo simulations allowing us to
generate many statistically representative weather years. For the investigated
realisations (weather years) we study deviations of production from demand
under different wind capacities, and introduce different scenarios where
flexibility options like storage and transmission is available. Our analysis
shows that simulated loss values are reduced significantly by cooperation and
any mode of flexibility. Combining storage and transmission leads to even more
synergies and helps to stabilise production levels and thus adequacy of
renewable power systems.
