  Demand response management has become one of the key enabling technologies
for smart grids. Motivated by the increasing demand response incentives offered
by service operators, more customers are subscribing to various demand response
programs. However, with growing customer participation, the problem of
determining the optimal loads to be curtailed in a microgrid during
contingencies within a feasible time frame becomes computationally hard. This
paper proposes an efficient approximation algorithm for event-based demand
response management in microgrids. In event-based management, it is important
to curtail loads as fast as possible to maintain the stability of a microgrid
during the islanded mode in a scalable manner. A simple greedy approach is
presented that can rapidly determine a close-to-optimal load curtailment scheme
to maximize the aggregate customer utility in milliseconds for a large number
of customers. This paper further derives a novel theoretical guarantee of the
gap between the proposed efficient algorithm and the optimal solution (that may
be computationally hard to obtain). The performance of algorithm is
corroborated extensively by simulations with up to thousands of customers. For
the sake of practicality, the proposed event-based demand response management
algorithm is applied to a feeder from the Canadian benchmark distribution
system. The simulation results demonstrate that the proposed approach
efficiently optimizes microgrid operation during islanded mode while
maintaining appropriate voltage levels and network constrains.
