An intelligent control approach to home energy management under forecast uncertainties

This paper proposes an optimization-based control strategy for home energy management. In order to simplify the home architecture, we put forward a grid-connected microgrid, which is comprised of PV panels, battery-based energy storage system, and critical loads and controllable loads. The objective of minimizing the operation costs and maximizing the utilization of renewable energy is achieved by a model predictive control strategy for scheduling the behaviours of the components in the microgrid. The proposed framework takes into account the predictions of load demand, PV generations and electricity price. A case study is employed to assess the performance under different forecast precisions of the proposed strategy and two other strategies used before, and the simulation results are presented and discussed.