The occurrence of extreme weather events seems to be on the rise, causing system outages and leaving customers without power supply for long time periods. Considerable research has been done to explore the use of distributed energy resources in distribution system restoration post extreme weather event. Due to the global clamor for reduced carbon emissions, emphasis has been placed on the use of renewable stationary power sources such as solar photovoltaic systems and more affordable mobile power sources such as rented electric vehicles to supply as much load as possible till grid supply is restored. This thesis models the resilience level of a typical distribution system having rooftop solar PV system, electric buses and electric vans as distributed energy resources post extreme weather event. These electric vehicles are supplied by transportation and logistics companies that have little or no use of these vehicles post extreme weather event. The location of rooftop solar and the number of electric vehicles is randomized and applied to different network reconfiguration topologies to evaluate the Expected Energy Not Served (EENS) using Monte Carlo Simulation. A base case scenario without electric vehicle integration and a second scenario with electric vehicle integration was considered using this simulation. The appropriate network reconfiguration topology with minimum value of EENS was obtained from generated results. The EENS value of the second scenario was further optimized using dynamic programming as a third scenario. This optimization approach also provides the minimum number of electric vans and buses needed to give minimized EENS when certain constraints are applied. Comparative analysis of the three scenarios is then done to demonstrate the need for use of rented electric vehicles in the enhancement of system resilience post extreme weather event.