  In this manuscript we continue the thread of [M. Chertkov, F. Pan, M.
Stepanov, Predicting Failures in Power Grids: The Case of Static Overloads,
IEEE Smart Grid 2011] and suggest a new algorithm discovering most probable
extreme stochastic events in static power grids associated with intermittent
generation of wind turbines. The algorithm becomes EXACT and EFFICIENT
(polynomial) in the case of the proportional (or other low parametric) control
of standard generation, and log-concave probability distribution of the
renewable generation, assumed known from the wind forecast. We illustrate the
algorithm's ability to discover problematic extreme events on the example of
the IEEE RTS-96 model of transmission with additions of 10%, 20% and 30% of
renewable generation. We observe that the probability of failure may grow but
it may also decrease with increase in renewable penetration, if the latter is
sufficiently diversified and distributed.
