Model predictive control based home energy management system in smart grid

Involving end-users in Demand Side Management (DSM) programs with home energy management systems (HEMS) is an important requirement in realizing the smart grid. In smart grids, advanced communication technologies provide an opportunity to communicate with customers expeditiously. Optimizing the demand side consumption yields economical benefits to both the utility and customer. The HEMS helps the customers to optimize their household appliances' operation. This paper presents the application of model predictive control (MPC) on the HEMS model in order to arrive at the optimal operational decisions when the inputs are subject to variations. Reduction in the total customer's energy cost is achieved. Additionally, the results show increase in customers' revenue from selling the generated and stored energy to the utility.