  Autonomous microgrid planning is a Mixed-Integer Non Convex decision problem
that requires to consider investments in both distribution and generation
capacity and represents significant computation challenges. We proposed in a
previous publication a deterministic Second-Order Cone (SOC) relaxation of this
problem that made it computationally tractable for realsize cases. However,
this problem is subject to considerable uncertainty emanating from load
consumption, RES-based generation and contingencies. In this paper, we thus
present a robust optimization approach that extends our previous work by
including load related uncertainty at the cost of a substantial increase of the
computational burden. The results show that significantly higher investment and
operational costs are incurred to account for the load related uncertainty.
