RISK-ORIENTED PROVISION OF ELECTROMAGNETIC COMPATIBILITY Kangozhin1, D. Insepov2

Abstract

The modern development of railway transport and the implementation of digital technologies in energy systems impose increased requirements for ensuring electromagnetic compatibility (EMC) of railway energy infrastructure. The relevance of the study is determined by the need to reduce the number of failures in automated control systems (ACS) under electromagnetic interference (EMI) and to increase equipment reliability. The aim of the study is to develop a comprehensive approach to ensuring EMC of railway transport objects using modern monitoring methods and mathematical modeling. The objectives include analyzing existing EMC methods and identifying their limitations, developing a mathematical model of the electromagnetic environment, investigating the effectiveness of hardware-software complexes for monitoring and managing EMC, and proposing methods for equipment protection against EMI. As a result of the research, a mathematical model of the electromagnetic environment at railway facilities was developed, and the software-measuring complex "PIK-EMC" was created to predict the reliability of SMART ACS systems. Experimental surveys of substations with harsh electromagnetic environments were conducted, EMI sources and transmission channels were identified, and the effectiveness of protection using hybrid filters was assessed. Modeling results demonstrated the high efficiency of hybrid filters in reducing current and voltage waveform distortions and damping resonance phenomena in the system. The study concludes that integrating mathematical modeling, hardware-software monitoring, and equipment protection significantly improves the reliability of SMART ACS systems. The results have both theoretical and practical significance: EMC assessment and management methods were refined, new regulatory approaches and software products with high commercialization potential were developed, and implementation on railway facilities is feasible. Future work includes enhancing EMC prediction methods, expanding software functionality, and industrial deployment of the developed technologies.