  The size distributions of power outages are shown to depend on the stress, or
the proximity of the load of an electrical grid to complete breakdown. Using
the data for the U.S. between 2002-2017, we show that the outage statistics are
dependent on the usage levels during different hours of the day and months of
the year. At higher load, not only are more failures likely, but the
distribution of failure sizes shifts, to favor larger events. At a finer
spatial scale, different regions within the U.S. can be shown to respond
differently in terms of the outage statistics to variations in the usage
(load). The response, in turn, corresponds to the respective bias towards
larger or smaller failures in those regions. We provide a simple model, using
realistic grid topologies, which can nonetheless demonstrate biases as a
function of the applied load, as in the data. Given sufficient data of small
scale events, the method can be used to identify vulnerable regions in power
grids prior to major blackouts.
