  Keeping the balance between supply and demand is a fundamental task in power
system operational planning practices. This task becomes particularly
challenging due to the deepening penetration of renewable energy resources,
which induces a significant amount of uncertainties. In this paper, we propose
a chance-constrained Unit Commitment (c-UC) framework to tackle challenges from
uncertainties of renewables. The proposed c-UC framework seeks cost-efficient
scheduling of generators while ensuring operation constraints with guaranteed
probability. We show that the scenario approach can be used to solve c-UC
despite of the non-convexity from binary decision variables. We reveal the
salient structural properties of c-UC, which could significantly reduce the
sample complexity required by the scenario approach and speed up computation.
Case studies are performed on a modified 118-bus system.
