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AI and ML Adaptive Smart-Grid Energy Management Systems: Exploring Advanced Innovations
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Author(s): S. Saravanan (Department of Electrical and Electronics Engineering, B.V. Raju Institute of Technology, Narsapur, India), Richa Khare (Amity School of Applied Sciences, Amity University, Lucknow, India), K. Umamaheswari (Department of Electrical and Electronics Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, India), Smriti Khare (Amity School of Applied Sciences, Amity University, Lucknow, India), B. S. Krishne Gowda (Department of Commerce, Government College for Women, Chintamani, India)and Sampath Boopathi (Department of Mechanical Engineering, Muthayammal Engineering College, Namakkal, India)
Copyright: 2024
Pages: 31
Source title:
Principles and Applications in Speed Sensing and Energy Harvesting for Smart Roads
Source Author(s)/Editor(s): Luay Taha (The Pennsylvania State University, Altoona, USA)and Sohail Anwar (The Pennsylvania State University, Altoona, USA)
DOI: 10.4018/978-1-6684-9214-7.ch006
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Abstract
The chapter explores the transformative role of artificial intelligence (AI) and machine learning (ML) in shaping smart energy management systems (SEMS) and predicts innovations by 2030. It discusses AI principles in energy optimization, predictive analytics in smart grids, and renewable energy integration through AI-driven strategies. The chapter also addresses critical aspects like predictive maintenance, consumer-centric solutions, cybersecurity challenges, ethical considerations, and regulatory frameworks for responsible AI implementation. By examining challenges and prospects, it provides insights into the dynamic future of energy management driven by AI and ML advancements.
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