Intelligent HEMS Based on Transformer and Hybrid PSO Scheduling Algorithm

In the context of growing environmental concerns, Home Energy Management Systems (HEMS) play a crucial role in promoting energy efficiency. This paper proposes an intelligent HEMS that leverages the transformer model for high-precision electricity usage prediction and the Hybrid Particle Swarm Optimization (HPSO) algorithm for optimal energy scheduling. The system takes into account device characteristics, electricity prices, and user preferences. It features a user-friendly graphical interface and incorporates large language models (LLMs) for enhanced voice interaction. Experimental results show that the transformer-based prediction improves accuracy, while the HPSO-based scheduling enhances energy efficiency and cost-effectiveness. With the integration of photovoltaic systems, this system offers a sustainable solution for home energy management, contributing to energy conservation and emission reduction.