  This paper envisions a new control architecture for the protective relay
setting in future power distribution systems. With deepening penetration of
distributed energy resources at the end users level, it has been recognized as
a key engineering challenge to redesign the protective relays in the future
distribution system. Conceptually, these protective relays are the discrete
ON/OFF control devices at the end of each branch and node in a power network.
The key technical difficulty lies in how to set up the relay control logic so
that the protection could successfully differentiate heavy load and faulty
operating conditions. This paper proposes a new nested reinforcement learning
approach to take advantage of the structural properties of distribution
networks and develop a new set of training methods for tuning the protective
relays.
