Automated Energy Management for Sustainable and Cost-Efficient Households: A Forecasting and Optimization Approach

Effective home energy management is essential for achieving sustainability and cost efficiency. This study introduces a novel automated system that not only forecasts energy consumption but also optimizes household device scheduling, offering a comprehensive approach to home energy management. Unlike existing solutions that often focus solely on monitoring or prediction, this system uniquely integrates real-time energy forecasting with intelligent device scheduling to actively reduce energy costs and environmental impact. By addressing the challenges of rising electricity costs and unpredictable energy usage patterns, the system empowers households to make informed decisions, reducing financial burdens while promoting sustainability. The system combines multiple modules to streamline energy management: real-time energy consumption data are collected using sensors and analyzed using the SARIMAX model for accurate energy forecasting. A hybrid approach employing the Greedy algorithm and XGBoost optimizes device scheduling, ensuring efficient energy use without compromising user convenience. These models were rigorously tested, refined, and integrated into a user-friendly Flutter-based interface, enhancing practical applicability. Performance evaluation highlights the system's effectiveness. The forecasting model achieved a Mean Absolute Error (MAE) of 1.74, a Mean Squared Error (MSE) of 4.92, a Root Mean Squared Error (RMSE) of 2.22, and a Mean Absolute Percentage Error (MAPE) of 23.81%. The optimization model further improved outcomes with an MAE of 0.24, MSE of 0.31, RMSE of 0.56, and an R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> Score of 0.97. This study advances the field by providing a fully integrated, data-driven energy management solution that not only predicts consumption but also actively optimizes it. The practical significance lies in its ability to deliver measurable cost savings and environmental benefits, offering a scalable and user-friendly tool for energy-conscious households.