  Under-Frequency Load Shedding (UFLS) schemes are the last resort to contain a
frequency drop in the grid by disconnecting part of the demand. The allocation
methods for selecting feeders that would contribute to the UFLS scheme have
traditionally relied on the fact that electric demand followed fairly regular
patterns, and could be forecast with high accuracy. However, recent integration
of Distributed Generation (DG) increases the uncertainty in net consumption of
feeders which, in turn, requires a reformulation of UFLS-allocation methods to
account for this uncertainty. In this paper, a chance-constrained methodology
for selecting feeders is proposed, with mathematical guarantees for the
disconnection of the required amount of load with a certain pre-defined
probability. The correlation in net-load forecasts among feeders is explicitly
considered, given that uncertainty in DG power output is driven by
meteorological conditions with high correlation across the network.
Furthermore, this method is applicable either to systems with conventional UFLS
schemes (where relays measure local frequency and trip if this magnitude falls
below a certain threshold), or adaptive UFLS schemes (where relays are
triggered by control signals sent in the few instants following a contingency).
Relevant case studies demonstrate the applicability of the proposed method, and
the need for explicit consideration of uncertainty in the UFLS-allocation
process.
