  We study a random conductance problem on a $d$-dimensional discrete torus of
size $L > 0$. The conductances are independent, identically distributed random
variables uniformly bounded from above and below by positive constants. The
effective conductance $A_L$ of the network is a random variable, depending on
$L$, and the main result is a quantitative central limit theorem for this
quantity as $L \to \infty$. In terms of scalings we prove that this nonlinear
nonlocal function $A_L$ essentially behaves as if it were a simple spatial
average of the conductances (up to logarithmic corrections). The main
achievement of this contribution is the precise asymptotic description of the
variance of $A_L$.
