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Optimizing Energy Systems Using Machine Learning and Artificial Intelligence
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Author(s): Praveen Kumar Nalli (Department of Artificial Intelligence, Shri Vishnu Engineering College for Women, India), K. P. Manikandan (Department of Cyber Security, Madanapalle Institute of Technology and Science, India), G. Padmapriya (Department of Computing Technologies, School of Computing, SRM Institute of Science and Technology, Kattankulatur, India), Dhowmya Bhatt (Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Ghaziabad, India), Nayanjyoti Talukdar (Department of Mechanical Engineering, Jorhat Institute of Science and Technology, Assam, India)and R. Premkumar (Department of Electronics and Instrumentation Engineering, Sri Sairam Engineering College, Chennai, India)
Copyright: 2025
Pages: 22
Source title:
Integrating Artificial Intelligence Into the Energy Sector
Source Author(s)/Editor(s): Abdelkader Mohamed Sghaier Derbali (Taibah University, Saudi Arabia)
DOI: 10.4018/979-8-3693-7112-1.ch023
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Abstract
This chapter discusses the potentially transformative role of ML and AI technologies to improve energy systems in terms of efficiency, reliability, and sustainability. Some of the applications of AI and ML in energy systems are advanced algorithms, predictive modeling, and online data analysis. The field of power optimization and fault detection systems is a significant area of focus. The chapter explores advanced energy pricing techniques, including reinforcement learning, deep learning for renewable energy integration, IoT-enabled predictive maintenance, and ethical challenges in these areas. Case studies and real-life insights demonstrate the potential of AI in energy management to enhance decision-making and promote sustainable energy development. The guidelines serve as a foundation for researchers, engineers, and policymakers to harness the potential of AI to significantly transform the global energy landscape.
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