  Battery energy storage systems (ESS) are widely used in microgrids to
complement high renewables. However, the real-time energy management of
microgrids with battery ESS is challenging in two aspects: 1) the evolution
process of battery energy level is across-time coupled; 2) uncertainties
unavoidably arise in the forecasting process for renewable generation. In this
paper, a tube-based model predictive control (MPC) approach is innovatively
proposed in accommodating the real-time energy management of microgrids with
battery ESS. Firstly, a real-time operation model of battery, including the
degradation cost and time-aware SoC range, is proposed for the battery ESS. In
particular, the battery feature shallower-cheaper is depicted and the terminal
SoC requirement is achieved. Secondly, two cascaded MPC controllers are
designed in the proposed tube-based MPC, in which reference trajectories are
generated by the nominal MPC without uncertainties, and then the ancillary MPC
steers the actual trajectories to the nominal ones upon the realization of
uncertainties. Specifically, in this paper, the battery SoC is viewed as the
state variable of the system, while the generator power output and exchange
power with the utility are seen as control variables. Lastly, numerous case
studies demonstrate the effectiveness of the proposed approach, including both
the low and high penetration level of renewables. Additional Monte Carlo
simulations of consecutive 365 days show that the competitive ratio of the
proposed approach is excellently below 1.10.
