AI RESEARCH
Reinforcement learning-based dynamic cleaning scheduling framework for solar energy system
arXiv CS.LG
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ArXi:2603.07518v1 Announce Type: new Advancing autonomous green technologies in solar photovoltaic (PV) systems is key to improving sustainability and efficiency in renewable energy production. This study presents a reinforcement learning (RL)-based framework to autonomously optimize the cleaning schedules of PV panels in arid regions, where soiling from dust and other airborne particles significantly reduces energy output.