Model predictive control-based operation management for a residential microgrid with considering forecast uncertainties and demand response strategies

This study proposes a model predictive control (MPC)-based home energy management system for residential microgrid (RM) in which all related information such as the time-varying information of the load demand, electricity price and renewable energy generations, are all taken into account. A novel finite-horizon mixed-integer linear programming problem is iteratively formulated to investigate the optimal control actions of the RM under an MPC framework. Three case studies are conducted to discuss the technical and economic impacts of the responsive electrical and thermal loads, plug-in hybrid electric vehicles, and electrical and thermal energy storage units. Moreover, a sensitivity analysis is performed to demonstrate the superiority of the proposed approach when forecasts of related information are imperfect.