THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE ENERGY SECTOR
DOI:
https://doi.org/10.55640/Keywords:
artificial intelligence, electrical energy, smart grids, energy efficiency, digital transformation.Abstract
This article presents a scientific analysis of the application of artificial intelligence (AI) technologies in the energy sector, focusing on their role in improving efficiency and ensuring the reliability of power supply systems. The study examines the implementation of Al algorithms in electricity generation, transmission, and distribution processes to automate operations, reduce energy losses, and enhance system stability. Furthermore, the advantages of Al integration in smart grids, predictive maintenance, and real-time monitoring systems are discussed.
Both local and international experiences are analyzed, highlighting the prospects for adopting Al-based solutions within Uzbekistan's power industry. The findings demonstrate that the widespread use of Al technologies contributes to the rational use of energy resources, increases system reliability, and enhances overall economic efficiency.
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References
1. Normatov R.N., Mirzaaxmedov M.K. (2022). Elektr energiyasi sohasida sun'iy intellekt tizimlarning ahamiyati. Talqin va tadqiqotlar, №6.
2. Balamurugan M., Narayanan K., Raghu N., Arjun Kumar G.B., Trupti V.N. (2025). Role of artificial intelligence in smart grid - a mini review. Frontiers in Artificial Intelligence.
3. Ejiyi C.J., et al. (2025). Comprehensive review of artificial intelligence applications in renewable energy systems: current implementations and emerging trends. Journal of Big Data.
4. Адылов Я.Т., Рахмонов К.А. (2024). Цифровой прорыв: мировой опыт применения искусственного интеллекта в эксплуатации и контроле энергосистем. Цифровая экономика, №3.
5. Ministry of Energy of the Republic of Uzbekistan. (2023). Concept of digital transformation in the energy sector. Tashkent: Publishing House of the Ministry of Energy
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Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.
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