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Title |
Real-Time Energy Management of a Microgrid using MPC-DDQN Controlled V2H and H2V with Renewable Energy Integration |
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Author |
Ahmed Albugmi |
| Citation |
Vol. 26 No. 3 pp. 1-14 |
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Abstract |
This paper presents the design and implementation of an Intelligent?Home Energy Management System (IHEMS) in a smart home. The system is based on an economically decentralized hybrid concept that includes photovoltaic (PV) technology, a proton exchange membrane fuel cell (PEMFC), and a hydrogen refuelling station (HRS), which together serve as components to provide a reliable, secure, and clean power supply for a single, smart home. The proposed design enables power transfer between Vehicle-to-Home (V2H) and Home-to-Vehicle (H2V). This allows electric vehicles (EVs) to function as mobile energy storage at the grid, facilitating a more adaptable and autonomous grid. Indeed, our approach employs Double Deep Networks (DDQN), a particular variant of DQN, for adaptive control and forecasting. A Multi-Agent System (MAS) setup coordinates actions between home appliances, Energy Storage Systems (ESS), electric vehicles (EVs), and hydrogen power devices to ensure effective and cost-saving energy distribution for users of the smart grid. The design validation is carried out through MATLAB/Simulink-based?simulation using meteorological data from Tunis. The results prove that the V2H/H2V system, provided with AI-based learning?and hydrogen power technology, improves residential energy systems' utilization, reliability, and cost-effectiveness |
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Keywords |
Intelligent Home Energy Management; Hydrogen-Powered Energy Systems; Vehicle-to-Home and Home-to-Vehicle; Double Deep Q-Learning; Autonomous Hybrid Energy Framework; Multi-Agent System Coordination |
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