UDC 621.311.
DOI: 10.36871/ek.up.p.r.2024.09.13.012
Authors
Khava V. Uzieva,
Assistant of the Department of Electrical Engineering and Electric Drive, Federal State
Budgetary Educational Institution named after Academician Millionshchikov, Grozny, Russian
Federation
Umar G. Baymuradov,
Kadyrov Chechen State University, Assistant of the Department of Programming and Infocommunication
Technologies
Mustafa E. M. Taha,
Energy and electrical engineering. Department of Electric Power Systems and Networks, Postgraduate
student of the Federal State Budgetary Educational Institution "KGEU", General Director,
LLC "TMG" LLC "Taha Mustafa Group" Engineering and Project Management", Kazan,
Russian Federation
Abstract
The article discusses automated systems for diagnostics and monitoring of power generating equipment based on artificial intelligence (AI) technologies. Particular attention is paid to their advantages, including increased reliability, reduced operating costs and accident prevention. Key aspects of the operation of such systems are presented, including the use of machine learning algorithms training for sensor data analysis, predictive analytics and integration with SCADA systems. The challenges of implementation, such as high cost, the need to ensure cybersecurity and dependence on data quality, are discussed. Development prospects, including the use of digital twins, autonomous systems and distributed data analysis, are also considered. Automated systems based on AI are shown as a key element in improving the efficiency and sustainability of energy generation in the context of industrial digitalization.
Keywords
automated systems, diagnostics, monitoring, energy generating equipment, artificial intelligence, machine learning
