  Improving the reliability of power distribution systems is critically
important for both utilities and customers. This calls for an efficient service
restoration module within a distribution management system to support the
implementation of self-healing smart grid networks. The emerging smart grid
technologies, including distributed generators (DGs) and remote-controlled
switches, although enhance the self-healing capability and allow faster
recovery, pose additional complexity to the service restoration problem,
especially under cold load pickup (CLPU) conditions. In this paper, we propose
a novel two-stage restoration framework to generate restoration solutions with
a sequence of control actions. The first stage generates a restoration plan
that supports both the traditional service restoration using feeder
reconfiguration and the grid-forming DG-assisted intentional islanding methods.
The second stage generates an optimal sequence of switching operations to bring
the outaged system quickly to the final restored configuration. The problem is
formulated as a mixed-integer linear program that incorporates system
connectivity, operating constraints, and CLPU models. It is demonstrated using
a multi-feeder test case that the proposed framework is effective in utilizing
all available resources to quickly restore the service and generates an optimal
sequence of switching actions to be used by the operator to reach the desired
optimal configuration.
