Computational and Experimental Studies on the Efficiency of Combined Electromagnetic Shielding of the Magnetic Field of Overhead Power Lines

image_print
DOI
Journal Journal of Mechanical Engineering – Problemy Mashynobuduvannia
Publisher Anatolii Pidhornyi Institute of Power Machines and Systems
of National Academy of Science of Ukraine
ISSN  2709-2984 (Print), 2709-2992 (Online)
Issue Vol. 28, no. 3, 2025 (September)
Pages 72-85
Cited by J. of Mech. Eng., 2025, vol. 28, no. 3, pp. 72-85

 

Author

Ihor V. Bovdui, Anatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine (2/10, Komunalnykiv str., Kharkiv, 61046, Ukraine), e-mail: ibovduj@gmail.com, ORCID: 0000-0003-3508-9781

 

Abstract

To improve the efficiency of reducing the power frequency of the magnetic field generated by overhead power lines in residential buildings, experimental studies based on the results of 3D modeling when using a combined electromagnetic shield consisting of active and passive parts were conducted. The problem of designing a combined electromagnetic shield consisting of a robust active shielding system and an electromagnetic passive shield is solved on the basis of a multi-criteria antagonistic game between two players. The vector of game wins is calculated using the finite element calculation system COMSOL Multiphysics, and the game solution is calculated using particle multiswarm optimization algorithms. When designing combined electromagnetic shields, the coordinates of the spatial location of the shielding winding, currents and phases in the shielding windings of the robust active shielding system, as well as the geometric dimensions and thickness of the electromagnetic passive shield, were calculated. The results of experimental studies of the effectiveness of magnetic field shielding using 3D modeling for a residential building and a power line, when using combined electromagnetic shielding with active and passive parts, are given. For the first time, in order to increase the effectiveness of a combined electromagnetic shield, which consists of active and passive parts, and is designed to reduce the industrial frequency of the magnetic field created by overhead power lines in residential buildings, experimental studies using 3D modeling were conducted. According to the results of experimental studies, the effectiveness of shielding the output magnetic field was determined. It was found that the shielding coefficient of the electromagnetic passive shield is more than two units, and the effectiveness of the system with an active shield is more than four units, and for a system with a combined electromagnetic passive and active shield it is more than 10 units. The possibility of reducing the level of magnetic field induction in a residential building from power lines when using combined electromagnetic passive and active shielding to a level safe for the population is proven.

 

Keywords: magnetic field, 3D modeling of combined electromagnetic passive and active shielding, experimental studies.

 

Full text: Download in PDF

 

References

  1. Hardell, L. (2017). World Health Organization, radiofrequency radiation and health – a hard nut to crack (Review). International Journal of Oncology, vol. 51, pp. 405–413. https://doi.org/10.3892/ijo.2017.4046.
  2. Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., & Jemal, A. (2024). Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a Cancer Journal for Clinicians, vol. 74, iss. 3, pp. 229–263. https://doi.org/10.3322/caac.21834.
  3. (2011). IARRC classifies radiofrequency electromagnetic fields as possibly carcinogenic to humans: Press release No. 2008. International Agency for Research on Cancer, 6 p. https://www.iarc.who.int/wp-content/uploads/2018/07/pr208_E.pdf.
  4. (2013). Directive 2013/35/EU of the European Parliament and of the Council of 26 June 2013 on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (electromagnetic fields). http://data.europa.eu/eli/dir/2013/35/oj.
  5. (2002). IEEE standard for safety levels with respect to human exposure to electromagnetic fields, 0–3 kHz. In: IEEE Std C95.6-2002, pp. 1–64. https://doi.org/10.1109/IEEESTD.2002.94143.
  6. Ghanim, T. H., Kamil, J. A., & Mutlaq, A. H. (2022). The influence of the mixed electric line poles on the distribution of magnetic field. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), vol. 10, no. 2, pp. 292–301. https://doi.org/10.52549/ijeei.v10i2.3572.
  7. Canova, A. & Giaccone, L. (2018). Real-time optimization of active loops for the magnetic field minimization. International Journal of Applied Electromagnetics and Mechanics, vol. 56, pp. 97–106. https://doi.org/10.3233/jae-172286.
  8. Canova, A. & Giaccone, L. (2017). High-performance magnetic shielding solution for extremely low frequency (ELF) sources. CIRED International Conference & Exhibition on Electricity Distribution, vol. 2017, iss. 1, pp. 686–690. https://doi.org/10.1049/oap-cired.2017.1029.
  9. Canova, A., Giaccone, L., & Cirimele, V. (2019). Active and passive shield for aerial power lines. 25th International Conference on Electricity Distribution (3–6 June 2019, Madrid), paper 1096, 5 p. https://www.cired-repository.org/server/api/core/bitstreams/e782355b-54df-4be1-9964-3e614f13bf07/content.
  10. Bravo-Rodríguez, J., del-Pino-López, J., & Cruz-Romero, P. A (2019). Survey on optimization techniques applied to magnetic field mitigation in power systems. Energies, vol. 12, iss. 7, pp. 1332–1332. https://doi.org/10.3390/en12071332.
  11. Canova, A., del-Pino-Lopez, J. C., Giaccone, L., & Manca, M. (2015). Active shielding system for ELF magnetic fields. IEEE Transactions on Magnetics, vol. 51, iss. 3, pp. 1–4. https://doi.org/10.1109/tmag.2014.2354515.
  12. Rusanov, A. V., Subotin, V. N., & Khoryev, O. M. (2022). Effect of 3D shape of pump-turbine runner blade on flow characteristics in turbine mode. Journal of Mechanical Engineering – Problemy Mashynobuduvannia, vol. 25, no. 4, pp. 6–14. https://doi.org/10.15407/pmach2022.04.006.
  13. Kostikov, A. O., Zevin, L. I., & Krol, H. H. (2022). The optimal correcting the power value of a nuclear power plant power unit reactor in the event of equipment failures. Journal of Mechanical Engineering – Problemy Mashynobuduvannia, vol. 25, no. 3, pp. 40–45. https://doi.org/10.15407/pmach2022.03.040.
  14. Maksymenko-Sheiko, K. V., Sheiko, T. I., & Lisin, D. O. (2022). Mathematical and computer modeling of the forms of multi-zone fuel elements with plates. Journal of Mechanical Engineering – Problemy Mashynobuduvannia, vol. 25, no. 4, pp. 31–38. https://doi.org/10.15407/pmach2022.04.032.
  15. Hontarovskyi, P. P., Smetankina, N. V, & Ugrimov, S. V. (2022). Computational studies of the thermal stress state of multilayer glazing with electric heating. Journal of Mechanical Engineering – Problemy Mashynobuduvannia, vol. 25, no. 2, pp. 14–21. https://doi.org/10.15407/pmach2022.02.014.
  16. Sushchenko, O., Averyanova, Yu., Ostroumov, I. V., Kuzmenko, N. S., Zaliskyi, M., Solomentsev, O., Kuznetsov, B., Nikitina, T., Havrylenko, O., Popov, A., Volosyuk, V., Shmatko, O., Ruzhentsev, N., Zhyla, S., Pavlikov, V., Dergachov, K., & Tserne, E. (2022). Algorithms for design of robust stabilization systems. In: Gervasi, O., Murgante, B., Hendrix, E. M. T., Taniar, D., & Apduhan, B. O. (eds). Computational Science and Its Applications – ICCSA 2022. Lecture Notes in Computer Science. Springer, Cham, vol. 13375, pp. 198–213. https://doi.org/10.1007/978-3-031-10522-7_15.
  17. Ummels, M. (2010). Stochastic Multiplayer Games Theory and Algorithms. Amsterdam: Amsterdam University Press, 174 p.
  18. Ray, T. & Liew, K. M. (2002). A swarm metaphor for multiobjective design optimization. Engineering Optimization, vol. 34, no. 2, pp. 141–153. https://doi.org/10.1080/03052150210915.
  19. Xiaohui, H., Eberhart, R. C., & Yuhui, S. (2003). Particle swarm with extended memory for multiobjective optimization. Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS’03 (Cat. No. 03EX706). USA, Indianapolis, pp. 193–197. https://doi.org/10.1109/sis.2003.1202267.
  20. Hashim, F. A., Hussain, K., Houssein, E. H., Mabrouk, M. S., & Al-Atabany, W. (2021). Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Applied Intelligence, vol. 51, pp. 1531–1551. https://doi.org/10.1007/s10489-020-01893-z.

 

Received 10 March 2025

Accepted 10 May 2025

Published 30 September 2025