Real-Time Energy Management Optimization for Smart Household

The ubiquitous perception and interactive properties offered by Internet of Things (IoT) technology enable more active participation of residential users to achieve energy efficiency via various demand response (DR) strategies. In this paper, the energy management problem of a smart home consisting of renewable energy source (RES), energy storage system (ESS), a set of schedulable home appliances, and dynamic electricity tariff is formulated. A home energy management system (HEMS) is developed using the mixed integer linear programing (MILP) technique, aiming to solve both load scheduling problem of home appliances and the energy dispatch problem of utility grid under a single optimization framework in real-time. Some elements such as RES and ESS are assumed to be uncontrollable for more realistic modelling. By leveraging the peak shaving and energy storage capability of ESS, the proposed HEMS is able to minimize the energy cost required to satisfy the scheduled load demands without violating the operating constraints of smart home and the convenience level of users.