IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration - Sami Binyamin; Sami Ben Slama (AI)
The integration of renewable energy sources and electric vehicles has become a focal point for industries and academia due to its profound economic, environmental, and technological implications. These developments require the development of a robust intelligent home energy management system (IHEMS) to optimize energy utilization, enhance transaction security, and ensure grid stability. For this reason, this paper develops an IntelliGrid AI, an advanced system that integrates blockchain technology, deep learning (DL), and dual-energy transmission capabilities—vehicle to home (V2H) and home to vehicle (H2V). The proposed approach can dynamically optimize household energy flows, deploying real-time data and adaptive algorithms to balance energy demand and supply. Blockchain technology ensures the security and integrity of energy transactions while facilitating decentralized peer-to-peer (P2P) energy trading. The core of IntelliGrid AI is an advanced Q-learning algorithm that intelligently allocates energy resources. V2H enables electric vehicles to power households during peak periods, reducing the strain on the grid. Conversely, H2V technology facilitates the efficient charging of electric cars during peak hours, contributing to grid stability and efficient energy utilization. Case studies conducted in Tunisia validate the system’s performance, showing a 20% reduction in energy costs and significant improvements in transaction efficiency. These results highlight the practical benefits of integrating V2H and H2V technologies into innovative energy management frameworks.