Optimizing Home Energy Consumption with an Improved Subtraction-Average Based Optimizer Algorithm: A Smart Grid-Based Approach

With the increasing demand for electricity and the growing integration of renewable energy sources, optimizing household energy consumption has become a major challenge. Smart Grid (SG) technology emerges as a solution to improve energy efficiency through real-time monitoring and control of domestic energy consumption. In this context, Home Energy Management Systems (HEMS) play a crucial role in scheduling and optimizing the use of smart appliances. However, achieving an optimal balance between cost reduction, user comfort, and efficient appliance management remains complex. In this paper, we enhanced the Subtraction-Average-Based Optimizer (SABO) metaheuristic by developing a modified version, called the Modified Subtraction-Average-Based Optimizer (MSABO), and applied it to energy consumption optimization in a HEMS that incorporates solar photovoltaic energy (SPVE). The goal is to minimize energy consumption while improving the quality of service in terms of cost reduction, Peak-to-Average Ratio (PAR), and user discomfort (UD) under Time-of-Use (TOU) tariffs. To evaluate the effectiveness of this new approach, we compared MSABO with the original SABO, the Genetic Algorithm (GA), and an unscheduled scenario, simulating both a single home and multiple homes. The results demonstrate that MSABO outperforms all other approaches.