Smart scheduling solutions for home energy management in residential systems

As smart grids and renewable energy sources become more prevalent, demand response (DR) has the potential to play an increasingly significant role in balancing demand and supply while also offering economic benefits to consumers. This paper presents an approach to optimal energy scheduling within home energy management (HEM) programs by integrating a DR strategy to reduce electricity costs. The developed model is determined as a mixed integer linear programming (MILP) problem to model smart home devices, including solar photovoltaic (PV) panels, energy storage systems (ESS), electric vehicles (EV), and heating-ventilation-air conditioning (HVAC). By utilizing the MILP model and day-ahead data, the HEM system dynamically adjusts the operations of home devices to reduce daily energy costs. The feasibility of the developed model is demonstrated through a typical smart home, which shows significant improvements in household cost reductions. As a result, DR integration can be a sustainable way to manage household energy consumption, encouraging wider deployment of HEM programs and supporting the transition to a more efficient and resilient power grid.