  The mathematical problem of the static storage optimisation is formulated and
solved by means of a variational analysis. The solution obtained in implicit
form is shedding light on the most important features of the optimal exercise
strategy. We show how the solution depends on different constraint types
including carry cost and cycling constraint. We investigate the relation
between intrinsic and stochastic solutions. In particular we give another proof
that the stochastic problem has a "bang-bang" optimal exercise strategy. We
also show why the optimal stochastic exercise decision is always close to the
intrinsic one. In the second half we develop a perturbation analysis to solve
the stochastic optimisation problem. The obtained approximate solution allows
us to estimate the time value of the storage option. In particular we find an
answer to rather academic question of asymptotic time value for the mean
reversion parameter approaching zero or infinity. We also investigate the
differences between swing and storage problems. The analytical results are
compared with numerical valuations and found to be in a good agreement.
