  Residential consumers have become active participants in the power
distribution network after being equipped with residential EV charging
provisions. This creates a challenge for the network operator tasked with
dispatching electric power to the residential consumers through the existing
distribution network infrastructure in a reliable manner. In this paper, we
address the problem of scheduling residential EV charging for multiple
consumers while maintaining network reliability. An additional challenge is the
restricted exchange of information: where the consumers do not have access to
network information and the network operator does not have access to consumer
load parameters. We propose a distributed framework which generates an optimal
EV charging schedule for individual residential consumers based on their
preferences and iteratively updates it until the network reliability
constraints set by the operator are satisfied. We validate the proposed
approach for different EV adoption levels in a synthetically created digital
twin of an actual power distribution network. The results demonstrate that the
new approach can achieve a higher level of network reliability compared to the
case where residential consumers charge EVs based solely on their individual
preferences, thus providing a solution for the existing grid to keep up with
increased adoption rates without significant investments in increasing grid
capacity.
