The integration of Artificial Intelligence (AI) into Smart Grid Management Systems (SGMS) has emerged as a transformative approach to enhance the efficiency, reliability, and sustainability of electrical power distribution networks. This paper explores the current state and future prospects of AI applications within the context of SGMS. It begins by outlining the challenges faced by traditional grid management, such as grid congestion, power losses, and the variability of renewable energy sources. The paper then delves into the various AI technologies that are being employed to address these challenges, including machine learning for predictive maintenance, optimization algorithms for load balancing, and deep learning for anomaly detection. Furthermore, the paper discusses the benefits and limitations of AI integration in SGMS, considering factors such as data privacy, cybersecurity, and the ethical implications of AI decision-making. The study concludes with a forward-looking perspective on the potential of AI to revolutionize the way electricity is managed and distributed in the future.
Jackson, O. Integration of Artificial Intelligence in Smart Grid Management Systems. Transactions on Engineering and Technology, 2022, 4, 30. https://doi.org/10.69610/j.tet.20220623
AMA Style
Jackson O. Integration of Artificial Intelligence in Smart Grid Management Systems. Transactions on Engineering and Technology; 2022, 4(1):30. https://doi.org/10.69610/j.tet.20220623
Chicago/Turabian Style
Jackson, Olivia 2022. "Integration of Artificial Intelligence in Smart Grid Management Systems" Transactions on Engineering and Technology 4, no.1:30. https://doi.org/10.69610/j.tet.20220623
APA style
Jackson, O. (2022). Integration of Artificial Intelligence in Smart Grid Management Systems. Transactions on Engineering and Technology, 4(1), 30. https://doi.org/10.69610/j.tet.20220623
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