  Higher penetration of renewable generation will increase the demand for
adequate (and cost-effective) controllable resources on the grid that can
mitigate and contain the contingencies locally before it can cause a
network-wide collapse. However, end-use constraints can potentially lead to
load unavailability when an event occurs, leading to unreliable demand response
services. Sensors measurements and knowledge of the local load dynamics could
be leveraged to improve the performance of load control algorithms. In the
context of hierarchical frequency response using ensemble of switching loads,
we present a metric to evaluate the fitness of each device in successfully
providing the ancillary service. Furthermore a fitness-based assignment of
control set-points is formulated which achieves reliable performance under
different operating conditions. Monte Carlo simulations of ensembles of
electric water heaters and residential air-conditioners are performed to
evaluate the proposed control algorithm.
