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The integration of Artificial Intelligence (AI) in smart grid communication networks promises significant advancements in energy management and distribution. This paper explores the transformative potential of AI in optimizing the efficiency, reliability, and sustainability of smart grids. Key applications of AI, such as machine learning algorithms for demand forecasting, predictive analytics for fault detection, and optimization techniques for energy distribution, are discussed in detail. AI's role in managing decentralized energy resources like solar panels and wind turbines is also examined, highlighting its ability to enhance the use of renewable energy sources. The paper identifies the primary benefits of AI integration, including improved efficiency, enhanced reliability, and greater sustainability. However, challenges such as data privacy and security, technical complexity, and interoperability are also addressed. To overcome these hurdles, future research directions are proposed, focusing on the development of advanced AI algorithms, real-time data processing, robust security measures, and effective human-AI collaboration. By addressing these challenges and leveraging advanced AI techniques, the paper concludes that smart grids can become more efficient, reliable, and sustainable, ultimately transforming the energy sector. DOI: https://doi.org/10.52783/tjjpt.v45.i02.6648
Purushottam Kumar Maurya (2024) studied this question.