MPC-based Optimal Control of Battery Management System in Residential Application

In the evolving field of residential energy management, optimizing energy use while minimizing costs has become increasingly critical. This paper explores the problem of optimizing a home energy management system by using Model Predictive Control (MPC) to boost economic efficiency and battery longevity. By integrating market prices, historical energy demand, and solar data into the MPC algorithm, it manages energy storage predictively. Additionally, the incorporation of the parameter that controls the discharge rate allows for the smoothing of the control signal. The study examines operational parameters, disturbance responses, and system configurations. The developed algorithm minimizes electricity costs and extends battery life, offering homeowners predictive savings and energy management insights with a minimal user interface.