Stochastic Model Predictive Control for economic/environmental operation management of microgrids

Microgrids are subsystems of the distribution grid which comprises generation capacities, storage devices and controllable loads, which can operate either connected or isolated from the utility grid. In this work, microgrid management system is developed in a stochastic framework. Uncertainties due to fluctuating demand and generation from renewable energy sources are taken into account and a two-stage stochastic programming approach is applied to efficiently optimize microgrid operations while satisfying a time-varying request and operation constraints. Mathematically, the stochastic optimization problem is stated as a mixed-integer linear programming problem, which can be solved in an efficient way by using commercial solvers. The stochastic problem is incorporated in a Model Predictive Control (MPC) scheme to further compensate the uncertainty though the feedback mechanism. Simulations show the effective performance of the proposed approach.