Real-Time Energy Consumption Optimization Using AI-Based Home Energy Management: A Comparative Study

Abstract

With the growing demand for sustainable and efficient energy use, there is an urgent need for advanced technologies that can manage home energy consumption. In this paper, The Design and Development of an Artificial Intelligence-Based Home Energy Management System (AI-HEMS), the system was proposed to optimize energy usage and reduce energy waste. The system utilizes machine learning algorithms to predict energy consumption patterns and optimize energy usage in real-time. The AI-HEMS consists of several components, including sensors, and actuators, to monitor and control the energy consumption of different household appliances. To test the validity on the claim that AI-HEMS are more reliable and effective in achieving Energy management and cost reduction in comparison to non-AI HEMS, Data was derived from three systems across a given time by the researcher from the same household using the same appliances. The first data set was from a traditional home system without HEMS, the second data set was from with the use of non-AI HEMS, the third data set was derived with the use of AI-HEMS. As seen by this research the AI-HEMS made a substantial reduction in the cost of energy Consumption and energy wastage when compared to other systems. The results of this research can provide valuable insights for the development of future energy management systems and contribute to the sustainable use of energy resources.