  Community microgrids offer many advantages for power distribution systems.
When there is an extreme event happening, distribution systems can be
seamlessly partitioned into several community microgrids for uninterrupted
supply to the end-users. In order to guarantee the system reliability,
distributed energy resources (DERs) should be sized for ensuring generation
adequacy to cover unexpected events. This paper presents a comprehensive
methodology for DERs selection in community microgrids, and an economic
approach to meet the system reliability requirements. Algorithms of discrete
time Fourier transform (DTFT) and particle swarm optimization (PSO) are
employed to find the optimal solution. Uncertainties of load demand and
renewable generation are taken into consideration. As part of the case study, a
sensitivity analysis is carried out to show the renewable generation impact on
DERs' capacity planning.
