Improvement of architecture for electricity metering system on railway transport

Introduction. In the context of the global digital transformation of railway transport and the transition from discrete parameter recording to the creation of digital twins of energy systems, it has become increasingly critical to implement systematic modernisation of Automated Information and Measurement System for Commercial Electricity Metering of JSC “Russian Railways”, in order to close technological gaps and ensure predictive control of energy consumption and the technical condition of equipment. The purpose of the work is the development and theoretical justification of the target architecture for a unified model of a digital platform integrating functions of legally significant commercial metering, predictive analytics (forecasting of electricity consumption and equipment failures), interaction with corporate systems, and external intelligent power grids.

Materials and methods. The research is based on a systematic analysis of the architectural-functional structure of the existing Information and Measurement System. Methods of structural modeling, comparative analysis of accounting subsystems and metering equipment fleet were used. Regulatory and legal framework was analysed, and a critical review of scientific publications was conducted.

Results. The study identified key limitations of the existing Information and Measurement System: technological fragmentation, diversity of equipment fleet, insufficient level of reporting automation. Weak integration with the corporate software environment and low rates of adaptation to the concept of intelligent power grids were noted. The current infrastructure does not provide monitoring of energy distribution from source to consumer and lacks predictive analytics functionality. The obtained results served as the basis for forming the target model of a unified digital platform. A four-level architecture for the system is proposed.

Discussion and conclusion. The necessity of transitioning to a unified digital platform integrating predictive analytics functions and seamless interaction with various systems is substantiated. The proposed solution creates a foundation for developing digital twins of energy objects, reducing operational costs and commercial losses.

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