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Shahmoradi H, Doroudi A, Farrokhi M. A Novel Method to identify Coherent Generators using Graph Theory and Clustering. Journal of Iranian Association of Electrical and Electronics Engineers 2024; 21 (4) :113-121
URL: http://jiaeee.com/article-1-1648-en.html
Faculty of Engineering, Shahed University
Abstract:   (1320 Views)
 Power system stability, control, and design studies are time-consuming due to the formation of large size and heavy interconnection networks. Reduced ordered dynamic equivalent methods are thus so desirable for performing these studies. Simple equivalents are obtained by converting large and complex networks into smaller networks. One of the approaches to the problem of model reduction is to find coherency-based generator grouping and aggregation. In this method, first, based on network characteristics, each group of coherent generators is replaced with a dynamic equivalent, and then the dynamic equivalent of the generators is used in the studies of power networks. In this regard, in this article, using graph theory and clustering quality index, a novel method for finding coherent generators in a power network is presented. The proposed method is simple and the network admittance matrix is the only information required by this approach. The IEEE 39-bus network is used to show the effectiveness of the proposed approach. The comparison of the results with other research shows that the proposed method identifies the coherent generators with an acceptable approximation.

 

 
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Type of Article: Research | Subject: Power
Received: 2023/10/2 | Accepted: 2024/07/29 | Published: 2025/01/11

References
1. [1] L. Mariotto, H. Pinheiro, G. Cardoso, A.P. Morais, and A.R. Muraro, "Power system transient stability indices: An Algorithm Based on Equivalent Clusters of Coherent Generators", IET Generation, Transmission and Distribution, Vol 4, No. 11, p.p. 1223-1235, 2010. [DOI:10.1049/iet-gtd.2009.0647]
2. [2] [2] J. H. Chow, Ed., Power System Coherency and Model Reduction. New York: Springer-Verlag, 2013.
3. [3] [3] J. Quiros-Tortos, R. Sanchez-Garc, J. Brodzki, J. Bialek, and V. Terzija, "Constrained spectral clustering-based methodology for intentional controlled islanding of large-scale power systems", IET Generation, Transmission and Distribution, Vol. 9, No. 1, pp. 31-42, 2015. [DOI:10.1049/iet-gtd.2014.0228]
4. [4] [4] N. Xue and A. Chakrabortty, "Control inversion: A clustering-based method for distributed wide-area control of power systems", IEEE Control Network Systems, Vol. 6, No. 3, pp. 937 - 949, 2019. [DOI:10.1109/TCNS.2018.2888997]
5. [5] [5] D. Efimov, and S. Stashkevich, "Coherence indicators of generators for express assessment of electric power system transient stability", Rudenko International Conference of Methodological Problems in Reliability Study of Large Energy Systems", Vol. 384, 2023. [DOI:10.1051/e3sconf/202338401012]
6. [6] [6] M. Naglic, M. Popov, M. van der Meijden, and V. Terzija, "Synchronized measurement technology supported online generator slow coherency identification and adaptive tracking", IEEE Trans. Smart Grid, Vol. 11, No. 4, pp.3405-3417, 2020. [DOI:10.1109/TSG.2019.2962246]
7. [7] J. Machowski, J. W. Białek, and J. R. Bumby, "Power system dynamics and stability", Chichester, U.K., Wiley, 1997.
8. [8] N. Gacic, A.I. Zecvic, and D.D. Siljak, "Coherency recognition using epsilon decomposition", IEEE Trans. on Power System, Vol. 13, No.2, 1998, p.p.314-319 [DOI:10.1109/59.667342]
9. [9] S.S. Lamba, and R. Nath, "Coherency identification by the method of weak coupling", International Journal of Electrical power & Energy Systems, Vol. 7, No.4, pp.233-242, 1985. [DOI:10.1016/0142-0615(85)90026-2]
10. [10] M. A. Pai and R. P. Adgaonkar, "Electromechanical distance measure for decomposition of power systems", Elect. Power Energy Syst., Vol. 6, pp. 249-254, Oct. 1984 [DOI:10.1016/0142-0615(84)90007-3]
11. [11] J. H. Chow, "New algorithms for slow coherency aggregation of large power systems", in Proc. Institute for Mathematics and Its Applications, pp. 95-115, 1993. [DOI:10.1007/978-1-4757-2433-2_4]
12. [12] D. Romeres, F. D¨orfler, and F. Bullo, "Novel results on slow coherency in consensus and power networks", in Proc. European Control Conf. (ECC), pp. 1-6., 2013. [DOI:10.23919/ECC.2013.6669400]
13. [13] نادری، ک. حسامی نقشبندی، ع. "الگوریتمی جدید برای جزیرهبندی کنترلشده سیستمهای قدرت مبتنی بر خوشهبندی طیفی مقید"، نشریه مهندسی برق و الکترونیک ایران، سال 14، شماره 3، صفحات 41-54، 1396
14. [14] G. Bruno, E.M. Carlini, and C. Pisani,: "Signal processing techniques for sensing based generator coherency analysis", Int. J. Electr. Power Energy Syst., Vol. 104, pp. 215-221, 2019. [DOI:10.1016/j.ijepes.2018.06.020]
15. [15] M. Sadeghi, H. Akbari , T. Daemi, and S. Mousavi, "An innovative mode-based coherency evaluation method for data-driven controlled islanding in power systems", Electric Power Systems Research, Vol. 214, Part A, 2023. [DOI:10.1016/j.epsr.2022.108808]
16. [16] S. Yu and J. Shi, "Multiclass spectral clustering," in Proc. 9th International Conference on Computer Vision (ICCV 2003), 2003, pp. 313-319. [DOI:10.1109/ICCV.2003.1238361] [PMID]
17. [17] J. Zhu, "Power system applications of graph theory", New York: Nova Science Publishers, Inc., 2009.
18. [18] L. Ding, F. M. Gonzalez-Longatt, P. Wall, and V. Terzija, "Two-step spectral clustering controlled islanding algorithm", IEEE Trans. on Power System, Vol. 28, No.1, 2013, p.p.75-83. [DOI:10.1109/TPWRS.2012.2197640]
19. [19] I. Tyuryukanov; M. Popov; M. Meijden, and V.l Terzija, "Slow Coherency Identification and Power System Dynamic Model Reduction by using Orthogonal Structure of Electromechanical Eigenvectors", IEEE Trans. on Power System, Vol. 36, No.2, p.p.1482-1492, 2021 [DOI:10.1109/TPWRS.2020.3009628]
20. [20] G. Xu, and V. Vittal, "Slow coherency based cutset determination algorithm for large power systems", IEEE Trans. on Power System, Vol. 25, No.2, p.p.877-884., 2010. [DOI:10.1109/TPWRS.2009.2032421]
21. [21] Z. Wu and R. Leahy, "An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation", IEEE Trans. Pattern Analysis & Machine Intelligence, Vol. 15, No. 11, pp. 101-113., 1993. [DOI:10.1109/34.244673]
22. [22] J. Shi, J. Malic, "Normalized cuts and image segmentation", IEEE Trans. on Pattern Analysis & Machine Intelligence, Vol. 22, No. 8, p.p. 888-905., 2000. [DOI:10.1109/34.868688]
23. [23] حسین‫پور م. پروین، ح. "انتخاب خوشههای اولیه به کمک الگوریتمهای هوشمند برای مشارکت در خوشهبندی ترکیب"، نشریه مهندسی برق و الکترونیک ایران، سال 13، شماره 2، صفحات 163-184، 1395.‬‬‬‬‬‬
24. [24] Z. Liu, and M. Barahona, "Graph-based data clustering via multi-scale community detection", Applied Network Science, Vol. 5, No. 3, 2020. [DOI:10.1007/s41109-019-0248-7]
25. [25] J. Quiros-Tortos1, P. Wall, L. Ding and V. Terzija, "Determination of sectionalizing strategies for parallel power system restoration: A spectral clustering-based methodology", Electric Power System Research, Vol. 116, p.p. 381-390, 2014. [DOI:10.1016/j.epsr.2014.07.005]
26. [26] T. L. Baldwin, L. Mili, and A. G. Phadke, "Ward-type Equivalents for Transient Stability Analysis", IFAC Proc. Vol. 25, No. 1, pp. 439-443, 1992. [DOI:10.1016/S1474-6670(17)50493-0]
27. [27] F. Znidi, H. Davarikiaa nd K. Iqbal, "Modularity clustering based detection of coherent groups of generators with generator integrity indices", IEEE Power & Energy Society, General Meeting , July 2017. [DOI:10.1109/PESGM.2017.8273835]
28. [28] J. Asumadu, E.A. Frimpong and P. Y. Okyere, "Real time prediction of coherent generator groups", Journal of Electrical Engineering, Vol. 16, No.3, 2016.
29. [29] P. Demetriou, L. Hadjidemetriou, A. Kyriacou, E. Kyriakides, and C. Panayiotou, "Real-Time Identification of Coherent Generator Groups", IEEE Eindhoven PwerTech Conference, July 2015.. [DOI:10.1109/PTC.2015.7232619] [PMID] []
30. [30] C. Jin, W. Li, L. Liu, P. Liu and X. Wu, "A Coherency Identification Method of Active Frequency Response Control Based on Support Vector Clustering for Bulk Power System", Energies, Vol. 12, No. 16, 2019. [DOI:10.3390/en12163155]

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