Evaluating the Potential of Home Energy Management Systems

Abstract

This research study describes an integrated Home Energy Management System (HEMS) that uses thermal models and Model Predictive Control (MPC) to optimise energy use for user comfort, power availability, cost reduction, and equipment longevity. The system also schedules flexible, deferrable, and thermal appliances based on load and utilisation characteristics, considering the energy demand for the whole household. The HEMS accurately predicts and controls indoor temperatures using a thermal model, while the MPC framework optimises energy consumption using real-time weather forecasts. Load scheduling algorithms prioritise and manage devices based on their load characteristics and importance. In a laboratory, hardware implementation of the thermal model was monitored and controlled, including interior temperature and power availability, to assess the suggested method. Control activities affected user convenience, energy efficiency, and device operation. Results show that MPC and thermal models improve HEMS energy management. The technology efficiently controls indoor temperatures while maximising energy efficiency. Load scheduling optimises device operation, reducing energy waste and improving system performance. This work integrates thermal models, MPC, and load scheduling to improve household energy management. The findings enable energy-efficient residential building design, user comfort, and device optimisation.