This study proposes a hybrid AI-based framework for optimizing residential EV charging systems through the integration of Reinforcement Learning (RL), Linear Programming (LP), and real-time grid-aware scheduling..
This study proposes a hybrid AI-based framework for optimizing residential EV charging systems through the integration of Reinforcement Learning (RL), Linear Programming (LP), and real-time grid-aware scheduling..
The rapid growth of renewable energy and electric vehicles (EVs) presents new development opportunities for power systems and energy storage devices. This paper presents a novel integrated Green Building Energy System (GBES) by integrating photovoltaic-energy storage electric vehicle charging. .
Centre for Electric Energy and High Voltage, CoE for Robotics and Sensing Technologies, Faculty of Artificial Intelligence and Engineering, Multimedia University, Cyberjaya 63100, Malaysia Department of Computer Sciences, College of Computing and Information Technology, Shaqra University, Shaqra. .
Billion’s PV+BESS+EV microgrid solution integrates solar power, battery energy storage, and intelligent EV charging to deliver clean, stable, and cost-efficient energy for commercial, industrial, and remote applications. With decades of experience in energy infrastructure, we empower global users.
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