  Averaging principle is an effective method for investigating dynamical
systems with highly oscillating components. In this paper, we study three types
of averaging principle for stochastic complex Ginzburg-Landau equations.
Firstly, we prove that the solution of the original equation converges to that
of the averaged equation on finite intervals as the time scale $\varepsilon$
goes to zero when the initial data are the same. Secondly, we show that there
exists a unique recurrent solution (in particular, periodic, almost periodic,
almost automorphic, etc.) to the original equation in a neighborhood of the
stationary solution of the averaged equation when the time scale is small.
Finally, we establish the global averaging principle in weak sense, i.e. we
show that the attractor of original system tends to that of the averaged
equation in probability measure space as $\varepsilon$ goes to zero.
