Post-emergency reconfiguration of a distribution network as a method for restoring power supply to consumers
https://doi.org/10.21285/1814-3520-2023-1-74-82
Abstract
The work is aimed at solving the problem of using reconfiguration and additional reactive power sources to restore power to consumers of the medium-voltage distribution network in the case of emergency disconnections of connections by bus section circuit breakers. The reconfiguration problem for a 118-node test distribution network is solved using a high-speed algorithm involving the construction of a maximum spanning tree on a network graph as the basis for determining information about the composition of branches and chords of independent circuits necessary to restore power following disconnection. To ensure acceptable voltage levels following power restoration, additional reactive power sources determined using singular Jacobian matrix analysis methods are installed in the sensor nodes of the network. For the test circuit, the modes for single disconnections of individual sectional switches, including in dead-end sections, are analysed. By optimally reconfiguring the network in the normal mode, it is possible to reduce voltage deviations from 13% to 7%. For the modes caused by disconnections of individual bus section circuit breakers that lead to unacceptable voltage deviations, the set-down locations and reactive power of additional sources are selected. In the most severe of the considered disconnection scenarios, the installation of additional sources provided a reduction in voltage deviations from 18 to 8%. Thus, the methods proposed by the authors make it possible to restore the test network mode following emergency disconnections and ensure that the voltages in the network nodes are maintained within acceptable limits, both in normal and in post-emergency modes.
About the Authors
E. V. Karpova
Melentiev Energy Systems Institute SB RAS
Russian Federation
Russian Federation
Elena V. Karpova, Postgraduate Student, Melentiev Energy Systems Institute SB RAS
130 Lermontov St., Irkutsk 664033, Russia
I. I. Golub
Melentiev Energy Systems Institute SB RAS
Russian Federation
Russian Federation
Irina I. Golub, Dr. Sci. (Eng.), Professor, Leading researcher of the Department of Electric Power Systems
130 Lermontov St., Irkutsk 664033, Russia
References
1. Lin Yanling, Bie Zhaohong. Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and DG islanding. Applied Energy. 2018;210:1266-1279. https://doi.org/10.1016/j.apenergy.2017.06.059.
2. Ding Tao, Lin Yanling, Bie Zhaohong, Chen Chen. A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration. Applied Energy. 2017;199:205-216. https://doi.org/10.1016/j.apenergy.2017.05.012.
3. Zu Guoqiang, Xiao Jun, Sun Kai. Mathematical base and deduction of security region for distribution systems with DER. IEEE Transactions on Smart Grid. 2019;10(3):2892-2903. https://doi.org/10.1109/TSG.2018.2814584.
4. Uspensky M.I., Kyzrodev I.V. Power restoration methods in distribution networks. Syktyvkar: Komi Scientific Center of the Ural Branch of the Russian Academy of Sciences; 2010, 120 p. (In Russ.).
5. Guimaraes M.A.N., Castro C.A., Romero R. Distribution systems operation optimisation through reconfiguration and capacitor allocation by a dedicated genetic algorithm. IET Generation, Transmission & Distribution. 2010;4(11):1213-1222. https://doi.org/10.1049/iet-gtd.2010.0020.
6. Abubakar A.S., Ekundayo K.R., Olaniyan A.A. Optimal reconfiguration of radial distribution networks using im-proved genetic algorithm. Nigerian Journal of Technological Development. 2019;16(1):10-16.
7. https://doi.org/10.4314/njtd.v16i1.2.
8. Pereira B.R.J., Cossi A.M., Contreras J., Mantovani J.R.S. Multiobjective multistage distribution system planning using tabu search. IET Generation, Transmission & Distribution. 2014;8(1):35-45. https://doi.org/10.1049/iet-gtd.2013.0115.
9. Abdelaziz A.Y., Osama R.A., El-Khodary S.M. Reconfiguration of distribution systems for loss reduction using the hyper-cube ant colony optimisation algorithm. IET Genera-tion, Transmission & Distribution. 2012;6(2):176-187. https://doi.org /10.1049/iet-gtd.2011.0281.
10. Chang Chung-Fu. Reconfiguration and capacitor placement for loss reduction of distribution systems by ant colony search algorithm. IEEE Transactions on Power System. 2008;23(4):1747-1755. https://doi.org/10.1109/TPWRS.2008.2002169.
11. Kavousi-Fard A., Niknam T., Khooban M.H. Intelligent stochastic framework to solve the reconfiguration problem from the reliability view. IET Science, Measurement & Technology. 2014;8(5):245-259. https://doi.org/10.1049/iet-smt.2013.0106.
12. Wu Wu-Chang, Tsai Men-Shen. Application of enhanced integer coded particle swarm optimization for distribution system feeder reconfiguration. IEEE Transactions on Power Systems. 2011;26(3):1591-1599. https://doi.org/ 10.1109/TPWRS.2010.2094212.
13. Minieka E., Dekker M. Optimization algorithms for net-works and graphs. New York: John Wiley & Song; 1979, 356 р.
14. Golub I.I., Vojtov O.N., Boloev E.V., Semenova L.V. Urban distribution network reconfiguration algorithm. Izvestiya Rossijskoj akademii nauk. Energetika = Thermal Engineering. 2020;5:3-12. (In Russ.). https://doi.org/10.31857/S0002331020050052.
15. Golub I.I., Voitov O.N., Boloev E.V., Semenova L.V. Choice of short-term constant configuration of the distribution network. Izvestiâ vysših učebnyh zavedenij. Problemy ènergetiki = Power engineering: research, equipment, tech-nology. 2018;20(9-10):39-51. (In Russ.). https://doi.org/10.30724/1998-9903-2018-20-9-10-39-51.
16. Zhang Dong, Fu Zhengcai, Zhang Liuchun. An im-proved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems. Electric Power Systems Research. 2007;77(5-6):685-694. https://doi.org/10.1016/j.epsr.2006.06.005.
17. Gamm A.Z., Golub I.I. Sensors and weak places in electric power systems. Irkutsk: Melentiev Energy Systems Institute SB RAS; 1996, 99 p. (In Russ.).
18. Voitov O.N., Voropai N.I., Gamm A.Z., Golub I.I., Efimov D.N. Analysis of heterogeneities of electric power systems. Novosibirsk: Nauka; 256 p. (In Russ.).
19. Agarkov О.А., Voitov O.N., Voropai N.I., Gamm A.Z., Golub I.I. Two approaches to the analysis of weak points of electric power systems. Moscow: Vysshaya shkola; 1985, 536 p. (In Russ.).
20. Belov E.I. Influence of nodes’ and branches’ parameters on the sensitivity of a power system’s elements. Izvestiya NTTS Edinoi ehnergeticheskoi sistemy. 2018;2:88-95. (In Russ.).
21. Belov E.I., Latmanizova Yu.N., Sorokin E.V. Singular analysis application for determining sensory branches in electric power systems. Ehlektroehnergiya. Peredacha i raspredelenie. 2018;4:48-52. (In Russ.).
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For citations:
Karpova E.V., Golub I.I. Post-emergency reconfiguration of a distribution network as a method for restoring power supply to consumers. iPolytech Journal. 2023;27(1):74-82. https://doi.org/10.21285/1814-3520-2023-1-74-82
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