Home Energy Management System for Scheduling Appliances with New Metaheuristic

Smart Grid (SG) technology allows customers to manage their energy consumption inside their homes. Home energy management involves programming smart appliances for more efficient use. Although SG gives users more control, effective energy management remains a challenge, particularly when it comes to programming appliances efficiently. In this paper, we describe a Home Energy Management System (HEMS) that uses a meta-heuristic called Subtraction-Average-Based Optimizer (SABO). The use of SABO aims to optimize energy consumption by reducing electricity costs in a typical smart home with solar photovoltaic energy (SPVE). This metaheuristic approach has proven advantageous in simultaneously achieving many objectives, such as minimizing daily energy consumption costs, decreasing user discomfort (UD), and reducing the Peak-to-Average Ratio (PAR) for the consumer under time-of-use (TOU) tariffs. The simulations included a variety of homes and appliances, categorized by usage and type. Additionally, the results are compared with those obtained using the Genetic Algorithm (GA) to further evaluate the effectiveness of SABO. The results are significant and promising for the optimization problem addressed, both with and without SPVE.