Preview

iPolytech Journal

Advanced search

Justification of the need to improve emergency control systems for preventing disturbances of voltage stability in power systems

https://doi.org/10.21285/1814-3520-2022-2-297-309

Abstract

   This article is aimed at justifying the need to modernize the existing systems that ensure voltage stability in the Unified Power System of Russia under the conditions of its permanent development, structural complication and active implementation of distributed generation. To this end, an analysis of the existing systems of emergency control used in the Unified Power System of Russia was conducted by considering their efficiency during major system accidents, including those in 2005 and 2017. In addition, specific features of operating power system facilities in the northern part of the Irkutsk Oblast were investigated from the standpoint of voltage stability. The conducted analysis of the operation of emergency control systems in the context of system accidents, including possible incorrect actions, identified their following disadvantages: insufficient fault tolerance, weak adaptability to emergency disturbances (including abnormal situations), as well as a lack of coordination between local devices and the discreteness of regulation. These shortcomings can be eliminated by introducing intelligent automation systems based on artificial neural networks and machine learning, as well as high-performance multi-agent systems into the structure of the emergency management of the Unified Power System of Russia. The results obtained indicate the need to modernize the existing voltage stability systems operated in the Unified Power System of Russia, both their software and hardware components. The proposed implementation of intelligent systems is expected to improve the existing systems at the same time as maintaining the current effective hierarchical principles of emergency management.

About the Authors

I. S. Reutsky
Russian Academy of Sciences
Russian Federation

Ivan S. Reutsky, Postgraduate

Siberian Branch of the Russian Academy of Sciences

Melentiev Energy Systems Institute

664074

130, Lermontov St.

Irkutsk



V. G. Kurbatsky
Russian Academy of Sciences
Russian Federation

Viktor G. Kurbatsky, Dr. Sci. (Eng.), Professor, Chief Researcher

Siberian Branch of the Russian Academy of Sciences

Melentiev Energy Systems Institute

Department of Electric Power Systems No. 40

664074

130, Lermontov St.

Irkutsk



References

1. Müller S. C., Kubis A., Brato S., Häger U., Rehtanz C., Götze J. New applications for wide-area monitoring, protection and control. In: 3rd IEEE PES Innovative Smart Grid Technologies Europe. 2012. https://doi.org/10.1109/ISGTEurope.2012.6465657.

2. Lachs W. R. Controlling grid integrity after power system emergencies. In: IEEE Transactions on Power Systems. 2002; 17 (2): 445-450. https://doi.org/10.1109/TPWRS.2002.1007916.

3. Gerasimov A. S., Esipovich A. H., Koshcheev L. A., Shul'ginov N. G. Research of the states of the Moscow power system in the process of the accident in May 2005. Elektrichestvo. 2008;1:2-12. (In Russ.).

4. Makarov Y. V., Reshetov V. I., Stroev A., Voropai N. I. Blackout prevention in the United States, Europe, and Russia. Proceedings of the IEEE. 2005; 93 (11): 1942-1955. https://doi.org/10.1109/JPROC.2005.857486.

5. Voropaj N. I., Kurbackij V. G., Tomin N. V., Panaseckij D. A., Sidorov D. N., Zhukov A. V., et al. A set of intelligent tools to prevent major accidents in power systems. Novosibirsk: Nauka; 2016, 332 р. (In Russ.).

6. Allen E., Andersson G., Berizzi A., Boroczky S. Blackout experiences and lessons, best practices for system dynamic performance, and the role of new technologies. Final report. IEEE; 2007. Available from: https://www.researchgate.net/publication/272482692 [Accessed 14th September 2021].

7. Voropai N., Tomin N., Kurbatsky V., Panasetsky D., Sidorov D., Zhukov A. Development of computational intelligence-based algorithms of preventing voltage collapse in power systems with a complex multi-loop structure. In: IEEE PES Asia-Pacific Power and Energy Engineering Conference. 2016. https://doi.org/10.1109/APPEEC.2016.7827553.

8. Voropai N. I., Efimov D. N., Mayakov D. V., Klepikov S. A., Smirnov S. S. Accident in the energy power system of Siberia on June 27, 2017. In: Metodicheskie voprosy issledovaniya nadezhnosti bol'shih sistem energetiki: sbornik nauchnyh trudov XX Mezhdunarodnogo nauchnogo ceminara = Methodological issues of studying the reliability of large energy systems: Collected scientific works of the 20 th International scientific seminar. 6 August 2018, Irkutsk. Irkutsk: Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences; 2018, р. 208-218. (In Russ.).

9. Sovalov S. A., Semenov V. A. Emergency control in power systems. Moscow: Energoatomizdat; 1988, 416 р. (In Russ.).

10. Zhdanov P. S. Issues of stability of electrical systems. Moscow: Energiya; 1979, 456 р. (In Russ.).

11. Panaseckij D. A., Tomin N. V., Kurbackij V. G., Voropaj N. I., Efimov D. N. Intelligent emergency control of power system modes. In: XII Vserossijskoe soveshchanie po problemam upravleniya: sbornik trudov = All-Russian meeting on control problems: collected works. 16–19 June 2014, Moscow. Moscow: V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences; 2014, р. 4770-4782. (In Russ.).

12. Voropai N. I., Negnevickij M, Tomin N. V., Panaseckij D. A., Kurbackij V. G., Retantz K., et al. An intelligent system to prevent major accidents in power systems. Elektrichestvo. 2014; 8: 19-31. (In Russ.).

13. Reuckij I. S., Kurbackij V. G., Tomin N. V. Prevention of voltage instability using artificial intelligence models. In: Metodicheskie voprosy issledovaniya nadezhnosti bol'shih sistem energetiki: sbornik nauchnyh trudov XX Mezhdunarodnogo nauchnogo seminara = Methodological issues of large energy system reliability research: Collected scientific works of the 20 th International scientific seminar (6 August 2018, Irkutsk. Irkutsk: Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences; 2018, р. 364-173. (In Russ.).

14. Kurbackij V. G., Reuckij I. S. Tomin N. V. Investigation of mode reliability of Irkutsk region energy system bottlenecks on example of the Bodaibo energy district. Metodicheskie voprosy issledovaniya nadezhnosti bol'shih sistem energetiki: sbornik nauchnyh trudov XX Mezhdunarodnogo nauchnogo seminara = Methodological issues of researching large energy system reliability: Collected scientific works of the 20 th International scientific seminar. 11–15 September 2017, Cholpon-Ata. Irkutsk: Melentiev Energy Systems Institute of the Siberian Branch of the Russian Academy of Sciences; 2017, iss. 68, p. 413-420. (In Russ.).

15. Reutskij I. S. Study of the organization problem of the operational dispatch control under the interaction of branches of the System Operator of the Unified Energy System JSC (JSC SO UES) – Regional Dispatch Office of the Energy System of the Irkutsk Region and Energy Saving Heating Systems. Elektroenergetika glazami molodezhi: sbornik nauchnyh trudov X Mezhdunarodnoj nauchnoj konferencii = Electric power industry through the eyes of youth: Collected scientific works of the 10 th International scientific conference 20 September 2019, Irkutsk. Irkutsk: Irkutsk National Research Technical University; 2019, р. 231-234. (In Russ.).

16. Baldick B., Chowdhury B., Dobson I., Dong Zhaoyang, Gou Bei, Hawkins D., et al. Initial review of methods for cascading failure analysis in electric power transmission systems IEEE PES CAMS task force on understanding, prediction, mitigation and restoration of cascading failures. In: IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century. 2008. https://doi.org/10.1109/PES.2008.4596430.

17. Tomin N. V., Kurbatsky V. G., Reutsky I. S. Hybrid intelligent technique for voltage/VAR control in power systems. The Institution of Engineering and Technology. 2019; 13 (20): 4724-4732. https://doi.org/10.1049/iet-gtd.2019.0214.

18. Zhukov A., Tomin N., Sidorov D., Kurbatsky V., Panasetsky D. On-line power systems security assessment using data stream random forest algorithm modification. In: Zelinka I., Vasant P., Duy V., Dao T. (eds.). Innovative Computing, Optimization and its Applications. Studies in Computational Intelligence. Cham: Springer; 2018, vol. 741, р. 183-200. https://doi.org/10.1007/978-3-319-66984-7_11.

19. Su Heng-Yi, Liu Tzu-Yi. Enhanced-online-random-forest model for static voltage stability assessment using wide area measurements. IEEE Transactions on Power Systems. 2018; 33 (6): 6696-6704. https://doi.org/10.1109/TPWRS.2018.2849717.

20. Li Xuan, Li Zhaowei, Guan Linlin, Zhu Ling, Liu Fusuo. Review on transient voltage stability of power system. In: IEEE Sustainable Power and Energy Conference. 2020; 940-947. https://doi.org/10.1109/iSPEC50848.2020.9351059.

21. Aquino-Lugo A. A., Klump R., Overbye T. J. A control framework for the smart grid for voltage support using agent-based technologies. IEEE Transactions on Smart Grid. 2011; 2 (1): 173-180. https://doi.org/10.1109/TSG.2010.2096238.

22. Belkacemi R., Babalola A., Zarrabian S. Experimental implementation of multi-agent system algorithm to prevent cascading failure after N-1-1 contingency in smart grid systems. In: IEEE Power & Energy Society General Meeting. 2015. https://doi.org/10.1109/PESGM.2015.7286630.

23. Xu Yinliang, Zhang Wei, Liu Wenxin, Ferrese F. Multi-agent-based reinforcement learning for optimal reactive power dispatch. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews). 2012; 42 (6): 1742-1751. https://doi.org/10.1109/TSMCC.2012.2218596.


Review

For citations:


Reutsky I.S., Kurbatsky V.G. Justification of the need to improve emergency control systems for preventing disturbances of voltage stability in power systems. iPolytech Journal. 2022;26(2):297-309. (In Russ.) https://doi.org/10.21285/1814-3520-2022-2-297-309

Views: 301


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2782-4004 (Print)
ISSN 2782-6341 (Online)