  This work considers energy management in a grid-connected microgrid which
consists of multiple conventional generators (CGs), renewable generators (RGs)
and energy storage systems (ESSs). A two-stage optimization approach is
presented to schedule the power generation, aimed at minimizing the long-term
average operating cost subject to operational and service constraints. The
first stage of optimization determines hourly unit commitment of the CGs via a
day-ahead scheduling, and the second stage performs economic dispatch of the
CGs, ESSs and energy trading via an hour-ahead scheduling. The combined
solution meets the need of handling large uncertainties in the load demand and
renewable generation, and provides an efficient solution under limited
computational resource which meets both short-term and long-term
quality-of-service requirements. The performance of the proposed strategy is
evaluated by simulations based on real load demand and renewable generation
data.
