Библиографическое описание:Improving the Reliability of the Protection of Electric Transport Networks : научное издание / Boris V. Malozyomov [et al.]. - Текст : непосредственный // World Electric Vehicle Journal. - 2025. - Т. 16, № 8. - P. 477. - ISSN 2032-6653, DOI 10.3390/wevj16080477.
Аннотация:<jats:p>In traction networks of mining enterprises, ensuring selective and sensitive protection remains an urgent task, especially in conditions of frequent starts of electric transport and possible cases of short circuits, lack of reliable grounding and increased spreading resistance. Standard methods—maximum current protection (MCP) and differential current protection (DCP)—demonstrate limited efficiency at operating currents less than 800 A, which is typical for remote sections of the contact network. The objective of this study is to develop and experimentally verify a method for adjusting the parameters of current and impulse protection, ensuring reliable shutdown of accidents at low values of short-circuit current without the need to replace equipment. The proposed method is based on transient processes modeled using differential equations and the introduction of a dynamic sensitivity coefficient reflecting the dependence of the setting on the circuit time constant. Universal response characteristics were constructed in normalized coordinates for BAT-49 and VAB-43 switches and RDSh-I and RDSh-II relays. Experiments have confirmed that the application of the method allows for reducing the tripping threshold to 600–650 A, increasing the selectivity of protection to 95% and reducing the probability of false tripping by more than two times compared to MCP/DCP. The response time remained within 35–45 ms, which meets the requirements for high-speed systems. The developed method is adapted to different network sections using the relative coordinates of the energy consumer on the supply section of the traction network and does not require complex digital equipment. This makes it especially effective in field conditions, where it is impossible to upgrade the protection using intelligent adaptive systems.</jats:p>
Держатель оригинала документа:Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia, Department “Technique and Technology of Mining and Oil and Gas Production”, Moscow Polytechnic University, 38, B. Semenovskaya St., Moscow 107023, Russia, Department of Automation and Control, Irkutsk National Research Technical University, Irkutsk 664074, Russia, Department of Electrotechnical Complexes, Novosibirsk State Technical University, Novosibirsk 630073, Russia, Department of Information Technology, Tomsk Polytechnic University, Tomsk 634050, Russia, Department of Navigation, Admiral Ushakov Maritime State University, Novosibirsk 630073, Russia, Department of Oil and Gas Engineering, Irkutsk National Research Technical University, Irkutsk 664074, Russia, Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, Krasnoyarsk 660041, Russia
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