Multi-time scale hierarchical predictive control for energy management of microgrid system with smart users

In this paper, a multi-time scale hierarchal model predictive control strategy is proposed to optimize energy management problem of a microgrid with multiple smart users. According to the power flow among different energy modules, a hierarchical system model and a multi-time scale hierarchal energy optimization management problem are established. The centralized controller in the upper layer is to optimize the charge/discharge time and energy of storage devices, controllable supply power adjustment and dispatch of the aggregators. The optimization problem in the lower layer is to meet users´ demands in real time. Meanwhile, in order to improve the disturbances caused by the randomness of renewable energy and variant loads, a multi-time scale optimization scheme is applied. At the slow scale, the upper optimization problem is solved, and the optimal energy scheduling in the long-term can be achieved. At the fast scale, the energy balance between supply and demand of smart users can be realized in the short-term. Finally, simulation results illustrate the effectiveness of proposed method.