  Electrical Distribution Systems are extensively penetrated with Distributed
Energy Resources (DERs) to cater the energy demands with the general perception
that it enhances the system's resilience. However, integration of DERs may
adversely affect the grid operation and affect the system resilience due to
various factors like their intermittent availability, dynamics of weather
conditions, non-linearity, complexity, number of malicious threats, and
improved reliability requirements of consumers. This paper proposes a
methodology to evaluate the planning and operational resilience of power
distribution systems under extreme events and determines the withstand
capability of the electrical network. The proposed framework is developed by
effectively employing the complex network theory. Correlated networks for
undesirable configurations are developed from the time series data of active
power monitored at nodes of the electrical network. For these correlated
networks, computed the network parameters such as clustering coefficient,
assortative coefficient, average degree and power law exponent for the
anticipation; and percolation threshold for the determination of the network
withstand capability under extreme conditions. The proposed methodology is also
suitable for identifying the hosting capacity of solar panels in the system
while maintaining resilience under different unfavourable conditions and
identifying the most critical nodes of the system that could drive the system
into non-resilience. This framework is demonstrated on IEEE 123 node test
feeder by generating active power time-series data for a variety of electrical
conditions using simulation software, GridLAB-D. The percolation threshold
resulted as an effective metric for the determination of the planning and
operational resilience of the power distribution system.
