Intelligent system for analysis of energy loss for ac traction networks for database updating
https://doi.org/10.46973/0201-727X_2024_1_176
Abstract
The paper considers methodology for creating intelligent systems for analyzing energy losses in traction networks including goals, objectives, functional composition, structure, as well as information bases of the intelligent system. The directions of research on optimization of power consumption modes, the structure of databases and knowledge bases are highlighted. In order of the developed intelligent system, the problem of assessing energy losses in traction networks and transformers and the efficiency of the train traction power supply system was studied. Factors influencing the components of power consumption have been identified, generalizing dependences of energy losses have been obtained for inclusion in the knowledge bases of expert systems.
About the Author
V. V. DomanskyRussian Federation
Vasily Valerievich Domansky, Candidate of Engineering Sciences, Associate Professor
Chair «Computer Science»
Rostov-on-Don
References
1. Kornienko, V. V. Electrification of railways. World trends and prospects (Analytical review) : monograph / V. V. Kornienko, A. V. Kotelnikov, V. T. Domansky. – Kyiv : Transport of Ukraine, 2004. – 196 p.
2. Improving the energy efficiency of electrical systems with traction loads / V. T. Domansky, I. V. Domansky, V. V. Domansky, G. A. Domanskaya // Proceedings of the 13<sup>th</sup> International Scientific and Expert Meeting on Information Technology for e-Education, Banja Luka, 24 –25. 9. 2021 / Pan-European University Apeiron. – Bosnia and Herzegovina/RS, Banja Luka, 2021. – P. 99–113. – ISBN 978-99976-34-80-1.
3. Nezevak, V.L. Improving the model of the influence of train schedule parameters on traction power consumption in direct and alternating current sections with type I and II track profile using regression models and neural networks / V. L. Nezevak // Bulletin of Transport of the Volga Region. – 2017. – No. 6. – P. 34–44. – ISSN 1997-0722.
4. Domansky, V. V. Information technologies of minimization of payment for electric power consumption of traction substations at differentiated tariffs : monograph / V. V. Domansky. – Rostov-on-Don : RSTU, 2017. – 114 р. – ISBN 978-5-88814-519-7.
5. Domansky, V. V. Information technologies of operation modes of traction power energy and supplying their energy systems / V. V. Domansky, G. A. Domanskaya, V. A. Vasenko // Vestnik Rostovskogo Gosudarstvennogo Universiteta Putey Soobshcheniya. – 2020. – No. 3. – Р. 154–165. – DOI: 10.46973/0201–727X_2020_3_154.
6. Markvard, K. G. Electricity supply of electrified railways / K. G. Markvard. – Moscow : Transport, 1982. – 528 p.
7. Karyakin, R. N. Traction networks of alternating current / R. N. Karyakin. – 2<sup>nd</sup> ed., rev. and add. – Moscow : Transport, 1987. – 279 p.
8. Osipova, V. E. Application of neural network methods for forecasting power consumption in railway transport / V. E. Osipova, D. A. Yakovlev // Modern information technologies and IT education. – 2022. – Vol. 18. – No. 1. – Р. 107–118. – DOI: 10.25559/SITITO.18.202201.107-118
9. Khashev, A.I. Combined simulation-analytical modeling in transport and logistics systems // A. I. Khashev, E. A. Mamaev, A. N. Guda // Vestnik Rostovskogo Gosudarstvennogo Universiteta Putey Soobshcheniya. – 2022. – No. 1 (85). – P. 117–125. – DOI: 10.46973/0201-727X_2022_1_117.
10. Domansky, V. V. Parameters of electric power supply of train traction for filling databases of simulation models / V. V. Domansky // Vestnik Rostovskogo Gosudarstvennogo Universiteta Putey Soobshcheniya. – 2023. – No. 2 (90). – P. 91–99. – DOI: 10.46973/0201-727X_2023_2_91.
11. Domansky, V. V. Information technologies and a method for calculating the risk of failure in case of drift of the technical condition of a traction transformer / V. V. Domansky // Vestnik Rostovskogo Gosudarstvennogo Universiteta Putey Soobshcheniya. – 2023. – No. 1 (89). – P. 264–273. – DOI: 10.46973/0201-727X_2023_1_264.
Review
For citations:
Domansky V.V. Intelligent system for analysis of energy loss for ac traction networks for database updating. Vestnik Rostovskogo Gosudarstvennogo Universiteta Putej Soobshcheniya. 2024;(1):176-185. (In Russ.) https://doi.org/10.46973/0201-727X_2024_1_176
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