INTEGRATION OF ARTIFICIAL INTELLIGENCE IN SMART GRIDS: IMPROVING ENERGY DISTRIBUTION AND MANAGEMENT
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Abstract
The rapid growth in energy demands and the shift toward renewable energy sources have necessitated smarter, more efficient power grids. Artificial Intelligence (AI) technologies are emerging as crucial tools for optimizing smart grid operations. This paper examines the role of AI in enhancing energy distribution, demand forecasting, and fault detection within smart grids. The study highlights how AI algorithms contribute to real-time decision-making, cost reduction, and sustainability, thereby transforming traditional energy networks into adaptive, resilient systems.
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1. Fang, X., Misra, S., Xue, G., & Yang, D. (2012). Smart Grid—The New and Improved Power Grid: A Survey. IEEE Communications Surveys & Tutorials, 14(4), 944–980.
2. Mohammadi, M., Al-Fuqaha, A., Sorour, S., & Guizani, M. (2018). Deep Learning for IoT Big Data and Streaming Analytics: A Survey. IEEE Communications Surveys & Tutorials, 20(4), 2923–2960.
3. Ghosh, S., Majumder, S., & Ghosh, A. (2021). Application of AI and IoT in Smart Grids: A Comprehensive Review. IEEE Access, 9, 100161–100183.