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Analysis of three-phase asymmetrical currents in the secondary voltage of signal change sensors in the power supply system using graph models

Azizjan AbubakirovNukus Mining Institute at Navoi State University of Mining and Technologies, Department of Electric power and automation of General Technology Faculty, Nukus city, Republic of Karakalpakstan, 230112, UzbekistanTimur KurbaniyazovKarakalpak State University named after Berdakh, Department of Electrical Engineering and Metrology of Physics Faculty, Nukus city, Republic of Karakalpakstan, 230112, UzbekistanMuratbay BekimbetovKarakalpak State University named after Berdakh, Department of Electrical Engineering and Metrology of Physics Faculty, Nukus city, Republic of Karakalpakstan, 230112, Uzbekistan
E3S Web of Conferencesjournal2024en
ABI

Аннотация

This article presents the principles of modeling three-phase asymmetrical currents in the form of secondary voltages of signal change sensors in the power supply system. The classical methods of signal transformation modeling do not provide the necessary accuracy due to the complexity in representing the interdependence between input and output quantities and parameters, as well as the difficulty in capturing the interchain dependencies and associated physical-technical effects. The analysis in this work focuses on the principles of signal transformation based on graph models, including the physical and technical effects of the three-phase primary current electromagnetic sensor that creates the interacting magnetic fields. The modifications to elements with nonlinear parameters and the values of the electric network currents in the power supply system during estimation have been considered as an object with concentrated parameters. In contrast to traditional single-phase current transformers, the complex transducing components, weight, and volume of the items are laborintensive when used in combined power measurement and control systems. They also do not provide the universality of the output value when interfacing with microprocessors and electronic technologies in intelligent systems.

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