Model Predictive Control of Energy Storage Systems for Power Tracking and Shaving in Distribution Grids

In this paper, a model predictive control (MPC) strategy is proposed to control the energy flows in a distribution network node (e.g., a distribution substation) equipped with an electric storage system (ESS) and serving a portion of the grid with high penetration of renewable energy sources (RES). The aim is to make the power flow at node level more controllable in spite of the presence of fluctuating distributed energy resources. In particular, the proposed control strategy is such that the controlled power flow at node level tracks the profile established on a day-ahead basis for efficient operation of the grid. That is achieved by letting the MPC controller decide the current storage power setpoint based on the forecasts of the demand and of the RES output. Theoretical results are reported on the stability of the proposed control scheme in a simplified setting foreseeing zero forecasting error. The performance of the system in the general case is then evaluated on a simulation basis. Simulations show the effectiveness in managing RES fluctuations in realistic settings.