Review of Key Elements Identification and Robustness Analysis of Power Grid based on Complex Network Theory

doi:10.23940/ijpe.22.05.p6.359368

Abstract

Abstract: Research on reliability of a power grid based on complex network theory has become a hot topic as the complexity of power grids increases with the continuous development of complex network theory. The research status of reliable operation of a power grid has been discussed by scholars from the perspectives of reliability, vulnerability, resilience and robustness. However, most studies are presented only from a single perspective. Thus, this paper comprehensively reviews power grid reliability research status from the perspective of key elements of identification and robustness analysis, which represent perturbation limit and tolerance to perturbation, respectively. Firstly, the basic theory and common evaluation indexes of complex network, as well as the influence of key elements and robustness on the reliable operation of power grid are introduced. Secondly, the current status of key element identification in power grids, the existing power grid elements importance ranking algorithms, its advantages and disadvantage, and evaluation criteria are discussed. Then, the present status of robustness analysis of power grids and the issues to be further explored are presented. Finally, the summary and outlook are given.

Key words: power grid, perturbation, complex network, key elements, robustness

Ying Huang, Linglin Gong, Jianguo Zhang, Haiwei Fan, and Yizhuo Zhang. Review of Key Elements Identification and Robustness Analysis of Power Grid based on Complex Network Theory [J]. Int J Performability Eng, 2022, 18(5): 359-368.

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References

1. Kebotogetse O., Samikannu R., andYahya A.Review of Key Management Techniques for Advanced Metering Infrastructure. International Journal of Distributed Sensor Networks, vol. 17, no. 8, pp. 15501477211041541, 2021.
2. Zhang, X. and Chi, K.T.Assessment of Robustness of Power Systems from a Network Perspective. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 5, no. 3, pp. 456-464, 2015.
3. Joung, J. and So, S. A Contrastive Analysis Study of Infographics Visualizing Big Data-based on Sases of Infographics on2003 Blackout in the United States and Canada. Journal of Design Convergence Study, vol. 42, pp. 258-272, 2013.
4. Rampurkar V., Pentayya P., Mangalvedekar H.A., andKazi F.Cascading Failure Analysis for Indian Power Grid. IEEE Transactions on Smart Grid, vol. 7, no. 4, pp. 1951-1960, 2016.
5. Xu Y.A Review of Cyber Security Risks of Power Systems: From Static to Dynamic False Data Attacks. Protection and Control of Modern Power Systems, vol. 5, no. 1, pp. 1-12, 2020.
6. Zhang G., Zhong H., Tan Z., Cheng T., Xia Q., andKang C.Texas Electric Power Crisis 2021 Warns of a New Mode of Blackout.CSEE Journal of Power and Energy Systems, 2022.
7. Mohamad F., Teh J., Lai C.M., andChen L.R.Development of Energy Storage Systems for Power Network Reliability: A Review. Energies, vol. 11, no. 9, pp. 2278, 2018.
8. An T., Tang G., andWang W.Research and Application on Multi‐terminal and DC Grids Based on VSC‐HVDC Technology in China. High voltage, vol. 2, no. 1, pp. 1-10, 2017.
9. Guo J., Liu W., Syed F.R., andZhang J.Reliability Assessment of a Cyber Physical Microgrid System in Island Mode. CSEE Journal of Power and Energy Systems, vol. 5, no. 1, pp. 46-55, 2019.
10. M Meske, C., Osmundsen, K.S., and Junglas, I. Designing and Implementing Digital Twins in the Energy Grid Sector. Journal of Manufacturing Science and Technology, vol. 29, pp. 36-52, 2020
11. Watts, D.J. and Strogatz, S.H.Collective Dynamics of ‘Small-world’ Networks. nature, vol. 393, no. 6684, pp. 440-442, 1998.
12. Barabási, A.L. and Albert, R.Emergence of Scaling in Random Networks. science, vol. 286, no. 5439, pp. 509-512, 1999.
13. Lambiotte R., Rosvall M., andScholtes I.From Networks to Optimal Higher-order Models of Complex Systems. Nature physics, vol. 15, no. 4, pp. 313-320, 2019.
14. Pagani, G.A. and Aiello, M.The Power Grid as a Complex Network: A Survey. Physica A: Statistical Mechanics and its Applications, vol. 392, no. 11, pp. 2688-2700, 2013.
15. Amani, A.M. and Jalili, M.Power Grids as Complex Networks: Resilience and Reliability Analysis.IEEE Access, 2021.
16. Saleh M., Esa Y., andMohamed A.Applications of Complex Network Analysis in Electric Power Systems. Energies, vol. 11, no. 6, pp. 1381, 2018.
17. Bai W.J., Zhou T., Fu Z.Q., Chen Y.H., Wu X., andWang B.H.Electric Power Grids and Blackouts in Perspective of Complex Networks. In 2006 International Conference on Communications, Circuits and Systems, IEEE, vol. 4, pp. 2687-2691, 2006.
18. Abedi A., Gaudard L., andRomerio F.Review of Major Approaches to Analyze Vulnerability in Power System. Reliability Engineering & System Safety, vol. 183, pp. 153-172, 2019.
19. Ding, Z. and Fei, M.Review of the Power Grid Model Vulnerability Based on Complex Network Theory. In International Computer Science Conference, Springer, Berlin, Heidelberg, pp. 105-113, 2012.
20. Mohseni-Bonab, S.M., Kamwa, I., Moeini, A., and Rabiee, A. Vulnerability Assessment in Power Systems: A Review and Representing Novel Perspectives. In2020 IEEE Power & Energy Society General Meeting (PESGM), IEEE , pp. 1-5, 2020.
21. Cuadra L.,Salcedo-Sanz, S., Del Ser, J., Jiménez-Fernández, S., and Geem, Z.W. A Critical Review of Robustness in Power Grids Using Complex Networks Concepts. Energies, vol. 8, no. 9, pp. 9211-9265, 2015.
22. Ma X., Zhou H., andLi Z.On the Resilience of Modern Power Systems: A Complex Network Perspective. Renewable and Sustainable Energy Reviews, vol. 152, pp. 111646, 2021.
23. Bachmann I.,Bustos-Jiménez, J., and Bustos, B. A Survey on Frameworks Used for Robustness Analysis on Interdependent Networks.Complexity, 2020.
24. Abdulkarem M., Samsudin K., Rokhani F.Z., andA Rasid, M.F. Wireless Sensor Network for Structural Health Monitoring: A Contemporary Review of Technologies, Challenges, and Future Direction. Structural Health Monitoring, vol. 19, no. 3, pp. 693-735, 2020.
25. Shi C., Peng Y., Zhuo Y., Tang J., andLong K.A New Way to Improve the Robustness of Complex Communication Networks by Allocating Redundancy Links. Physica Scripta, vol. 85, no. 3, pp. 035803, 2012.
26. Erdős, P. and Rényi, A.On the Evolution of Random Graphs. Publ. Math. Inst. Hung. Acad. Sci, vol. 5, no. 1, pp. 17-60, 1960.
27. Albert, R. and Barabási, A.L.Statistical Mechanics of Complex Networks. Reviews of modern physics, vol. 74, no. 1, pp. 47, 2002.
28. Chen Z., Wu J., Xia Y., andZhang X.Robustness of Interdependent Power Grids and Communication Networks: A Complex Network Perspective. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 65, no. 1, pp. 115-119, 2017.
29. Liu D., Chi K.T., andZhang X.Robustness Assessment and Enhancement of Power Grids from a Complex Network’s Perspective Using Decision Trees. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 5, pp. 833-837, 2019.
30. RAMIREZ-MARQUEZ, J.E., and ZIO, D.E.S.A.E. A Flow Importance Measure with Application to an Italian Transmission Power System. International Journal of Performability Engineering, vol. 6, no. 1, pp. 53, 2010.
31. Kinney R., Crucitti P., Albert R., andLatora V.Modeling Cascading Failures in the North American Power Grid. The European Physical Journal B-Condensed Matter and Complex Systems, vol. 46, no. 1, pp. 101-107, 2005.
32. Zhu X., Zhang W. M., Yu B., andGong W. G.Identification of Vulnerable Lines in Power Grid based on Complex Network Theory. inproceedings of the IEEE-Power-Engineering-Society General Meeting, pp. 1699-1704, Tampa, FL, 2007.
33. Bompard E., Pons E., andWu D.Extended Topological Metrics for the Analysis of Power Grid Vulnerability. IEEE Systems Journal, vol. 6, no. 3, pp. 481-487, 2012.
34. Du G., He L., andFang J.The Component Importance Evaluation of Power Converter Based on Complex Network. In2014 International Power Electronics and Application Conference and Exposition, IEEE, pp. 988-992, 2014.
35. Li Y.S., Ma D.Z., Zhang H.G., andSun Q.Y.Critical Nodes Identification of Power Systems Based on Controllability of Complex Networks. Applied sciences, vol. 5, no. 3, pp. 622-636, 2015.
36. Liu R., Zhang J., Dong Z., Li Y.Q., Tang X., Luo H., Jia J., andCheng L.Complex Network Theory Based Recognition of Power Grid Key Line. In2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), IEEE, pp. 770-774, 2015.
37. Liu B., Li Z., Chen X., Huang Y., andLiu X.Recognition and Vulnerability Analysis of Key Nodes in Power Grid Based on Complex Network Centrality. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 65, no. 3, pp. 346-350, 2017.
38. Li C., Kang Z., Yu H., andRi K.Identifying Key Nodes in the Power System Considering Node Properties. In AIP Conference Proceedings, AIP Publishing LLC, vol. 2122, no. 1, pp. 020002, 2019.
39. Li-Ya, H., Ping-Chuan, T., You-Liang, H., Yi, Z., and Xie-Feng, C. Node Importance Based on the Weighted K-order Propagation Number Algorithm. Acta Physica Sinica, vol. 68, no. 12, pp. 20190087, 2019.
40. Yang D.S., Sun Y.H., Zhou B.W., Gao X.T., andZhang H.G.Critical Nodes Identification of Complex Power Systems Based on Electric Cactus Structure. IEEE Systems Journal, vol. 14, no. 3, pp. 4477-4488, 2020.
41. Beyza J.,Garcia-Paricio, E., Ruiz, H.F., and Yusta, J.M. Geodesic Vulnerability Approach for Identification of Critical Buses in Power Systems. Journal of Modern Power Systems and Clean Energy, vol. 9, no. 1, pp. 37-45, 2020.
42. Koç Y., Warnier M., Kooij R.E., andBrazier F.M.A Robustness Metric for Cascading Failures by Targeted Attacks in Power Networks. In2013 10th IEEE International Conference on Networking, Sensing and Control (ICNSC), IEEE, pp. 48-53, 2013.
43. Feng H., Li S., andLi H.Identification of Key Lines for Multi-photovoltaic Power System Based on Improved Pagerank Algorithm. Frontiers in Energy Research, vol. 8, pp. 341, 2020.
44. Katz L.A New Status Index Derived from Sociometric Analysis. Psychometrika, vol. 18, no. 1, pp. 39-43, 1953.
45. Newman M.E.A Measure of Betweenness Centrality Based on Random Walks. Social networks, vol. 27, no. 1, pp. 39-54, 2005.
46. Estrada, E. and Rodriguez-Velazquez, J.A. Subgraph Centrality in Complex Networks. Physical Review E, vol. 71, no. 5, pp. 056103, 2005.
47. Poulin R., Boily M.C., andMâsse B.R.Dynamical Systems to Define Centrality in Social Networks. Social networks, vol. 22, no. 3, pp. 187-220, 2000.
48. Abdullah, A.M. and Butler-Purry, K. Secure Transmission Line Distance Protection during Wide Area Cascading Events Using Artificial Intelligence. Electric Power Systems Research, vol. 175, pp. 105914, 2019.
49. Schneider C.M., Moreira A.A., Andrade J.S., Havlin S., andHerrmann H.J.Mitigation of Malicious Attacks on Networks. Proceedings of the National Academy of Sciences, vol. 108, no. 10, pp. 3838-3841, 2011.
50. Kitsak M., Gallos L.K., Havlin S., Liljeros F., Muchnik L., Stanley H.E., andMakse H.A.Identification of Influential Spreaders in Complex Networks. Nature physics, vol. 6, no. 11, pp. 888-893, 2010.
51. Dou B.L., Wang X.G., andZhang S.Y.Robustness of Networks against Cascading Failures. Physica A: Statistical Mechanics and its Applications, vol. 389, no. 11, pp. 2310-2317, 2010.
52. Wang J.W.Robustness of Heterogenous Networks with Mitigation Strategy against Cascading Failures. Modern Physics Letters B, vol. 26, no. 14, pp. 1250087, 2012.
53. Ma T.L., Yao J.X., Qi C., Zhu H.L., andSun Y.S.Non-monotonic Increase of Robustness with Capacity Tolerance in Power Grids. Physica A: Statistical Mechanics and its Applications, vol. 392, no. 21, pp. 5516-5524, 2013.
54. Zhang, X. and Chi, K.T.Assessment of Robustness of Power Systems from a Network Perspective. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 5, no. 3, pp. 456-464, 2015.
55. Tu H., Xia Y., andChen X.Effect of Capacity Redundancy Disparity on Robustness of Power Grids. In2017 International Workshop on Complex Systems and Networks (IWCSN), IEEE, pp. 59-65, 2017.
56. Guo, W., Wang, H. and Wu, Z.Robustness Analysis of Complex Networks with Power Decentralization Strategy via Flow-sensitive Centrality against Cascading Failures. Physica A: Statistical Mechanics and its Applications, vol. 494, pp.186-199, 2018.
57. Tu H., Xia Y., Iu H.H.C., and Chen, X. Optimal Robustness in Power Grids from a Network Science Perspective. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 1, pp. 126-130, 2018.
58. Wang S., Zhang J., andYue X.Multiple Robustness Assessment Method for Understanding Structural and Functional Characteristics of the Power Network. Physica A: Statistical Mechanics and its Applications, vol. 510, pp. 261-270, 2018.
59. Wang S., Lv W., Zhao L., Nie S., andStanley H.E.Structural and Functional Robustness of Networked Critical Infrastructure Systems under Different Failure Scenarios. Physica A: Statistical Mechanics and its Applications, vol. 523, pp. 476-487, 2019.
60. Fang J., Zhang X., Wu J., andZheng Z.Robustness Analysis of Power Grids against Cascading Failures Based on a Multi-objective Algorithm. In2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, pp. 1-5, 2019.
61. Wang W., Song Y., Li Y., andJia Y.Research on Cascading Failures Model of Power Grid Based on Complex Network. In2020 Chinese Control And Decision Conference (CCDC), IEEE, pp. 1367-1372, 2020.
62. Ye, X. and Ying, X.Hybrid Attacks on Complex Networks in Redundancy and Workload View. Information Technology Journal, vol. 12, no. 15, pp. 3447, 2013.
63. Jun-Chun, M.A., Yong-jun, W.A.N.G., Ji-yin, S.U.N., and Shan, C.H.E.N. A Minimum Cost of Network Hardening Model Based on Attack Graphs. Procedia Engineering, vol. 15, pp. 3227-3233, 2011.
64. Li J., Wu J., Li Y., Deng H.Z., andTan Y.J.Attack Robustness of Scale-free Networks Based on Grey Information. Chinese Physics Letters, vol. 28, no. 5, pp. 058904, 2011.

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