This book is a comprehensive scientific and practical guide to the digital transformation of industrial power systems. This book explores how artificial intelligence, real-time monitoring, and predictive analytics are reshaping the management of electricity in energy-intensive industries with continuous production cycles—such as metallurgy, chemical processing, and cement manufacturing. The core motivation behind this book lies in a global industrial challenge: how to ensure energy efficiency, reliability, and operational stability while maintaining uninterrupted technological processes. Traditional methods of load control and energy optimization are no longer sufficient in an era defined by Industry 4.0, Smart Grid technologies, IoT integration, and cyber-physical systems (CPS). This book bridges classical electrical-engineering theory with the latest advances in AI-driven forecasting, SCADA/EMS/BEMS systems, digital twins, and machine-learning-based optimization, offering readers both theoretical depth and actionable engineering tools. Across six logically connected chapters, this book guides readers from the fundamental laws of power consumption and system reliability to advanced topics such as adaptive-predictive architectures, stochastic modeling of industrial loads, and multi-agent control for real-time decision-making. Mathematical models, algorithmic frameworks, and applied case studies demonstrate how enterprises can reduce losses, manage reactive power, and forecast demand with higher precision. Each section combines analytical rigor with implementation strategies that can be directly applied in industrial environments. This book’s novel contribution lies in its interdisciplinary integration of electrical engineering, system theory, data science, and artificial intelligence into one unified methodological framework. It introduces an integral indicator of energy efficiency tailored for continuous production and proposes a hybrid AI-based control architecture capable of self-learning and adaptation under uncertainty. Written for a broad professional audience, this book benefits energy engineers, researchers, graduate students, and decision-makers involved in power supply, automation, and digital-energy management. Policymakers and sustainability strategists find it valuable for understanding how intelligent control systems can support national goals in green energy transition, industrial modernization, and carbon-reduction strategies. By combining theoretical insight with real-world relevance, this book serves as both a reference manual and a visionary roadmap for designing the next generation of intelligent, stable, and energy-efficient industrial power systems—a critical step toward the sustainable factories of the future.

Rakhmonov Ikromjon Usmonovich is a doctor of Technical Sciences, professor, and head of the Department of Power Supply at Tashkent State Technical University (TSTU). His research focuses on increasing the efficiency of energy consumption in industrial enterprises, optimization of power supply systems, and intelligent energy management. He is the author of over 250 research publications, including 6 monographs and 124 scientific articles, of which 65 appeared in prestigious international journals and 59 in Scopus and Web of Science databases. Under his supervision, 7 doctoral dissertations have been successfully defended, and 3 Ph.D. students and 4 independent researchers are currently pursuing their research. Professor Rakhmonov is recognized as one of Uzbekistan’s leading scholars in industrial energy systems and digital power management.

Ushakov Vasiliy Yakovlevich is a doctor of Technical Sciences, professor, and honored worker of Science and Technology of Russia. He is currently a professor at Tomsk Polytechnic University (TPU). Formerly, he served as department head, director of the Research Institute, vice-rector for Scientific Work, and director of the Regional Energy Saving Center at TPU. He has authored more than 430 scientific papers and 27 monographs and textbooks (six published by Springer Verlag) and holds 38 invention certificates and patents. Under his leadership, 39 Candidate and 8 Doctoral dissertations were successfully defended. His research centers on energy efficiency, electric power systems, and optimization of electricity consumption in industrial enterprises.

Niyozov Numon Nizomiddinovich is an, Ph.D., associate professor at Tashkent State Technical University. His research activities focus on energy consumption forecasting, standardization, and efficiency improvement in industrial enterprises. He has published around 82 scientific works, including 2 monographs and 31 journal articles; among them, 17 are in international journals and 16 in Scopus and WoS proceedings. His work bridges applied power engineering and data-driven energy analysis for industrial optimization.

Kurbonov Nurbek Nurullo Ugli is an, Ph.D., associate professor at TSTU. He conducts research on digitalization of industrial enterprise management based on artificial intelligence, emphasizing efficiency enhancement, environmental performance, and energy forecasting. He has authored approximately 72 research papers, including 2 monographs and 29 scientific articles, with 13 published in international journals and 16 indexed in Scopus. His research contributes to the integration of AI and IoT technologies into Energy Management Systems (EMS).

Jalilova Dinora Anvarovna is an Ph.D., associate professor at TSTU. Her research focuses on AI-based digitalization of industrial enterprise management and improving environmental and energy indicators within Energy Management Systems. She has published about 69 scientific works, including 1 monograph and 27 articles, with 21 papers in international journals and 6 indexed in Scopus. She is an active researcher in the field of sustainable energy and intelligent automation.

Korjobova Makhzuna Fakhriddin Kizi is an, Ph.D., associate professor. She specializes in intelligent control systems in metallurgy, particularly in developing AI-based solutions for Electric Arc Furnaces to improve energy efficiency and electrode movement regulation. She has authored about 25 publications, including 1 monograph and 12 scientific articles, with 3 in reputable international journals and 5 in Scopus-indexed outlets. Her work contributes to the modernization of metallurgical energy systems through smart control technologies.