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Harnessing Artificial Intelligence for a Greener Future in Solar, Wind, and Hydrogen

Harnessing Artificial Intelligence for a Greener Future in Solar, Wind, and Hydrogen
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Author(s): G. Boopathy (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India), K. Jayakumar (Sri Sivasubramaniya Nadar College of Engineering, India), C. Suresh (Global Academy of Technology, India)and V. Srinivasan (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India)
Copyright: 2025
Pages: 26
Source title: Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green Hydrogen
Source Author(s)/Editor(s): Hind Hammouch (University Sidi Mohamed Ben Abdellah, Morocco)and Laeeq Razzak Janjua (WSB University, Poland)
DOI: 10.4018/979-8-3373-0045-0.ch017

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Abstract

Renewable energy sources have been the driver of innovation, with solar, wind, and the green hydrogen close to the top of the list. The addition of Artificial Intelligence (AI) to these systems enables faster development, improved scalability, and higher reliability for these systems. AI predicts weather patterns, optimizes panel orientation and allows for predictive maintenance of solar photovoltaic (PV) systems to maximize solar energy and minimize operational downtime and inefficiencies. AI optimizes the performance of wind turbines by optimizing accurate wind pattern forecasting and energy supply stabilization through intelligent grid integration via predictive analytics. Electrolysis processes are improved with AI, its energy efficiency is increased, and the green hydrogen is distributed and stored as well as possible. While barriers still exist in issues such as data privacy and computational demand, developments in edge computing and machine learning appear to bring about encouraging opportunities for moving past these barriers.

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