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AI and ML for Energy Management: Innovations and Challenges in a Sustainable Future
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Author(s): M. Gokuldhev (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), K. Vijayakumar (Panimalar Engineering College, India), M. Mercy Theresa (SRM Institute of Science and Technology, India), K. Sudha (RMD Engineering College, India), S. Nagarajan (R.M.K. Engineering College, India), R. Prasath (RMK College of Engineering and Technology, India)and P. J. Beslin Pajila (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India)
Copyright: 2025
Pages: 26
Source title:
Energy Efficient Algorithms and Green Data Centers for Sustainable Computing
Source Author(s)/Editor(s): P.J. Beslin Pajila (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), Belfin Robinson Vimala (University of North Carolina, USA), Y. Harold Robinson (Francis Xavier Engineering College, India)and C. Gopala Krishnan (GITAM University, India)
DOI: 10.4018/979-8-3373-0766-4.ch005
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Abstract
The rising international energy consumption and the necessity of looking for environment-friendly solutions have necessitated the use of technology such as AI and ML for the energy management. This paper provides a state-of-art review of AI and ML in energy efficiency and microgrid systems, smart grid, and renewable energy systems, industries, and smart buildings. AI and ML enable predictive modeling, realtime optimization, advanced control methodologies that enhance the energy efficiency, operation cost and facilitate the integration of renewable energy systems. The paper outlines some of the important methodologies like reinforcement learning, deep learning and optimization algorithms in energy systems and their limitations like data quality, model interpretability and scalability. The results imply that the use of AI and ML systems is crucial in determining the direction of the future of energy management and ensuring the sustainability of the process.
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