GIS-Analysis Of The Ural Power Grid Vulnerability To The Impact Of Sleet And Wind
Abstract
In this paper, we describe an experiment of complex power grid structure and wind and sleet mapping of territory using two different network indices: standard edge betweenness centrality and new author’s index – electrical grid centrality. Such analysis of the network allows to identify power lines with high load which could be vulnerable elements of the power grid. It is very important for strategic planning of power grids to reduce the risk of accidents by distributing loads across several lines so that they will be able to reserve each other. As a case territory for this research, we took the Ural united power system in Russia which is greatly exposed to different sleet and wind according to the statistics of the power grid operator. The degree of natural hazard consequences could be compensated by the network structure through alternative paths of energy supply or vice versa – increased if they are absent. At the same time, in this paper we consider that power grids have their own features from the graph theory point of view, for example multiple (parallel) edges, branches, different types of vertices. The existing index of edge betweenness centrality does not perfectly cope with them. We compare two indices characterizing power line importance within the system – betweenness centrality and electrical grid centrality and analyze the network structure features together with the spatial distribution of sleet and wind. As a result, we could identify bottlenecks in the study network. According to this study the most vulnerable power lines were detected, for example 500 kV Iriklinskaya CHP – Gazovaya and 500 kV Yuzhnouralskaya CHP-2 – Shagol power lines, that supply big cities such as Chelyabinsk and Orenburg and a bunch of industries around them.
About the Authors
Andrey M. Karpachevskiy
Lomonosov Moscow State University
Russian Federation
Russian Federation
Geography faculty, department of cartography and geoinformatics
Leninskie Gory 1, 119991, Moscow
Oksana G. Filippova
Lomonosov Moscow State University
Russian Federation
Russian Federation
Geography faculty, department of cartography and geoinformatics
Leninskie Gory 1, 119991, Moscow
Pavel E. Kargashin
Lomonosov Moscow State University
Russian Federation
Russian Federation
Geography faculty, department of cartography and geoinformatics
Leninskie Gory 1, 119991, Moscow
References
1. Atlas of natural and man-made hazards and emergency risks (2012). Moscow, Russia: Feoria Pub (in Russian).
2. Bugromenko V. N. (1987). Transport in territorial systems. (in Russian). Moscow: Nauka.
3. Chaitanya V.V.R.V., Mohanta D.K. and Reddy M.J.B. (2011). Topological analysis of eastern region of Indian power grid. In 10th International Conference on Environment and Electrical Engineering. 8-11 May 2011, Rome. Rome: IEEE, 449-453.
4. Chibryakov Ya.Yu. (2015). The development of cartographic methods for studies of the Russian railway network. Thesis (PhD). Moscow state university of Geodesy and Cartography (In Russian).
5. Crucitti P., Latora V. and Marchiori M. (2005). Locating critical lines in high-voltage electrical power grids. Fluctuation and Noise Letters, 2(5), 201-208.
6. Docs.cntd.ru (2015). Building acts 2.01.07-85 «Loads and impacts» [online] Available at: https://docs.cntd.ru/document/5200280 [Accessed 30 Apr. 2020] (in Russian).
7. Erdős P., Rényi A. (1959). On Random Graphs. I. Publicationes Mathematicae, 6, 290-297.
8. Faddeev A. (2016). Assessment of vulnerability of power systems of Russia, CIS countries and Europe to cascade accidents. Bulletin of Moscow University. Series 5: Geography, 1, 46-53 (in Russian).
9. Faybisovich D.L. (2012). Handbook of power systems design. Moscow: ENAS (in Russian).
10. FSK-EES.ru (2014). Standards of organization. [online] Available at: https://www.fsk-ees.ru/about/standards_organization [Accessed 20 Apr. 2020] (in Russian)
11. Garrison W.L. (1974). Connectivity of the Interstate Highway System. In: M.E. Eliot Hurst ed. Transportation Geography: Comments and Reading, New York: McGraw-Hill, 81-92.
12. Guimer R. and Amaral L.A.N. (2004). Modeling the world-wide airport network. The European Physical Journal B – Condensed Matter, 38(2), 381-385.
13. Hines P. and Blumsack S. (2008). A centrality measure for electrical networks. In: 41st Hawaii International Conference on Systems Science, 7-10 January 2008 Waikoloa, Big Island, HI, USA.
14. Kargashin P.E. Novakovskiy B.A., Prasolova A.I. and Karpachevskiy A.M. (2016). Study of the spatial configuration of power grids from satellite images. Geodesy and cartography, 3, 50-55. (In Russian).
15. Karpachevskiy A.M. and Filippova O.G. (2018). Mapping of emergency power systems based on open data. In: InterCarto/InterGIS 24, 19-22 July 2018, Petrozavodsk: Carelia science centre, 1, 202-211. (In Russian).
16. Karpachevskiy A.M. and Novakovskiy B.A. (2019). Opportunities of ArcGIS GIS tools usage for structural analysis of electrical networks. Geoinformatics, 2, 4-11. (In Russian).
17. Karpachevskiy A.M., Moskalev A.V. and Viktorov V.N. (2020). Classification and possible consequences of errors in vector mapping of power line routes in the Federal Grid Company’s geoinformation system. Energy of united grid, 3(52), 42-49. (In Russian).
18. Karpachevskiy A.M. (2018). Cartographic support of planning of development of regional electric networks. Thesis (PhD). Lomonosov Moscow state university. (In Russian).
19. Minenergo.gov. Blackouts. [online] Available at: https://minenergo.gov.ru/node/267 [Accessed 09 Sept. 2021] (in Russian).
20. Nasiruzzaman A.B.M., Akter M., Nahida M., Md Apel and Pota H.R. (2018). Network theory based power grid criticality assessment. In PEDES 2018: Proceedings of the 2018 IEEE International Conference on Power Electronics, Drives and Energy Systems, Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1-5.
21. Newman M. Networks. 2nd ed. Oxford: Oxford University Press.
22. Pagani A. and Aiello M. (2013). The power grid as a complex network: A survey. Physica A, 392(2013), 2688-2700.
23. PUE7.ru (2006). Wiring regulations [online] Available at: http://pue7.ru/pue7/sod.php [Accessed 25 Apr. 2020] (in Russian)
24. Rosas-Casals M., Valverde S. and Solé R.V. (2007). Topological vulnerability of the European power grid under errors and attacks. International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, 17(7), 2465-2475.
25. Scott J. and Carrington P.J. (2011). The SAGE Handbook of Social Network Analysis. Los-Angeles: SAGE publications.
26. Shabliy O.I. (1976). Intersectoral territorial systems (problems of methodology and theory). Lviv: Higher school. (In Russian).
27. Tarkhov S.A. (2005). Evolutionary morphology of transport networks. Smolensk-Moscow:Universum. (In Russian).
28. Tikunov V.S. (1997). Modelling in cartography. Moscow: Moscow University Publishing. (In Russian).
29. Watts D.J. and Strogatz S.H. (1998). Collective dynamics of «small-world» networks. Nature. 393 (6684), 440-442.
30. Yang Y., Nishikawa T., and Motter A.E. (2017). Small vulnerable sets determine large network cascades in power grid. In: Science, 358(6365), DOI: 10.1126/science.aan3184.
Review
Supporting agencies: This study was conducted within the framework of the state-ordered research theme of the Lomonosov Moscow State University, Cartography and Geoinformatics department, no. 121051400061-9 «Development of methods and technologies of cartography, geoinformatics and aerospace sensing in the research of nature and society».
For citations:
Karpachevskiy A.M., Filippova O.G., Kargashin P.E. GIS-Analysis Of The Ural Power Grid Vulnerability To The Impact Of Sleet And Wind. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2022;15(1):14-25. https://doi.org/10.24057/2071-9388-2021-082
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