  The increasing penetration of renewable energy resources in distribution
systems necessitates high-speed monitoring and control of voltage for ensuring
reliable system operation. However, existing voltage control algorithms often
make simplifying assumptions in their formulation, such as real-time
availability of smart meter measurements (for monitoring), or real-time
knowledge of every power injection information(for control).This paper
leverages the recent advances made in highspeed state estimation for real-time
unobservable distribution systems to formulate a deep reinforcement
learning-based control algorithm that utilizes the state estimates alone to
control the voltage of the entire system. The results obtained for a modified
(renewable-rich) IEEE34-nodedistributionfeeder indicate that the proposed
approach excels in monitoring and controlling voltage of active distribution
systems.
