International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Alayande Akintunde Samson1,2*, Olawale Popoola1, Vincent Mbey2

1 Centre for Energy & Electric Power, Department of Electrical Engineering, Tshwane University of Technology, Pretoria, 0002, South Africa

2 Deptartment of Electrical and Electronics Engineering, Faculty of Engineering, University of Lagos, Akoka, Yaba, Lagos, 23401, Nigeria

 

Download Citation: |
Download PDF


ABSTRACT

Formulation of faster frameworks for swift detection of coherent generators in a power system operating under a severe disturbance has been a serious issue for the effective operation of modern power grids. Providing an efficient solution to this problem becomes more compounded when combining the issue of island formation during the disturbance. This paper, therefore, focuses on proffering an alternative but simple approach to coherent generator identification as well as detecting islands in an interconnected power system operating under severe disturbances. The practical 330-kV network of the Nigerian power system and the standard IEEE 30-bus system are used as case studies to test the effectiveness of the suggested approach in this paper. Based on the structural topology of the network, the critical transmission element where the effect of the disturbance is most severe is first determined. The approach is then used to determine the coherency threshold for identifying similarities in the network rotor angles. The normalized bus coherency matrix based on the Euclidean distances for all rotor angles is then determined considering the increasing oscillations in the systems' stability parameters. The symmetrical component matrix is then extracted from the normalized bus coherency machine matrix, which is explored to determine a threshold value for identifying coherent pairs of generators. The N-1 contingency analysis with distinct coherent groups is created and the results before and after the implementation of coherency analysis and islanding scheme are presented. The results revealed an effective generation-to-load matching with four islands formation within the Nigerian system and three island formation within the IEEE 30-bus network. The results obtained when compared with the existing results show that the suggested approach is able to predict the coherent groups of generators as well as identifying the island formed faster and effectively to avoid voltage collapse in the practical power systems.


Keywords: Coherency identification, Coherent generators, Controlled islanding, Euclidian distances, Electrical topology.


Share this article with your colleagues

 


REFERENCES

  1. Aghamohammadi, M.R., Tabandeh, S.M. 2016. A new approach for online coherency identification in power systems based on correlation characteristics of generators rotor oscillations. International Journal of Electrical Power and Energy Systems 83, 470–484.

  2. Alayande, A.S., Jimoh, A.A.G., Yusuff, A.A. 2020. Identification of critical elements in interconnected power networks. Iranian Journal of Science and Technology - Transactions of Electrical Engineering, 44, 197–211.

  3. Amjady, N., Majedi, S.F. 2007. Transient stability prediction by a hybrid intelligent system. IEEE Transactions on Power Systems 22, 1275–1283.

  4. Arefi, M., Chowdhury, B. 2019. Coherency detection of generators using recurrence quantification analysis. Electric Power Systems Research 169, 162–173.

  5. Arrieta Paternina, M.R., Zamora-Mendez, A., Ortiz-Bejar, J., Chow, J.H., Ramirez, J.M. 2018. Identification of coherent trajectories by modal characteristics and hierarchical agglomerative clustering. Electric Power Systems Research 158, 170–183.

  6. Ayodele, T., Ogunjuyigbe, A., Oladele, O. 2015. Improving the transient stability of Nigerian 330 kv transmission network using static var compensation part I: the base study. Nigerian Journal of Technology 35, 155.

  7. Chow, J.H., Sanchez‐Gasca, J.J. 2019. Power system coherency and model reduction, power system modeling, computation, and control.

  8. Dabbagchi, I, Christie, R. 1993. IEEE 30-bus system. University of Washington. 1. Available: http://labs.ece.uw.edu/pstca/pf30/pg_tca30bus.htm.

  9. El-Arini, M.M.M., Fathy, A. 2011. Identification of coherent generators for large-scale power systems using fuzzy algorithm. WSEAS Transactions on Systems and Control 6, 229–238.

  10. Heidary, M., Alikhanlou, S., Aghamohammadi, M.R. 2014. Estimation of rotor angle based on operating variables measured by PMU.

  11. Jabari, F., Seyedi, H., Ravadanegh, S.N. 2017. Online aggregation of coherent generators based on electrical parameters of synchronous generators. 30th Power System Conference, PSC 2015 8–13.

  12. Jafarzadeh, S., Genc, I., Nehorai, A. 2021. Real-time transient stability prediction and coherency identification in power systems using Koopman mode analysis. Electric Power Systems Research 201, 107565.

  13. Jin, C., Li, W., Liu, L., Li, P., Wu, X. 2019. A coherency identification method of active frequency response control based on support vector clustering for bulk power system. Energies 12.

  14. Kundur, P. 2013. Power system stability and control, handbook of electrical power system dynamics: modeling, stability, and control. McGraw-Hill, Inc.

  15. Lin, Z., Wen, F., Ding, Y., Xue, Y., Liu, S., Zhao, Y., Yi, S. 2018. WAMS-Based coherency detection for situational awareness in power systems with renewables. IEEE Transactions on Power Systems 33, 5410–5426.

  16. Liu, T., Wen, J., Liu, X., Li, X. 2009. A fuzzy clustering method for coherent generator groups identification based on A-K. 1st International Conference on Sustainable Power Generation and Supply, SUPERGEN ’09 1–4.

  17. Nigerian Electricity Regulatory Commission (NERC). 2010. The grid code for the Nigeria electricity transmission index version II. 47–49.

  18. Padhi, S., Mishra, B.P. 2015. Solution of swing equation for transient stability analysis in dual-machine system. IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org ISSN 05, 34–39.

  19. Rogers, G. 2000. Power system oscillations. Springer Science & Business Media, LLC.

  20. Rogers, G. 2012. Power system oscillations. Springer Science & Business Media.

  21. Samuel, I.A., Katende, J., Awosope, C.O.A., Awelewa, A.A. 2017. Prediction of voltage collapse in electrical power system networks using a new voltage stability index. International Journal of Applied Engineering Research 12, 190–199.

  22. Soni, B.P., Saxena, A., Gupta, V., Surana, S.L. 2018. Identification of generator criticality and transient instability by supervising real-time rotor angle trajectories employing RBFNN. ISA Transactions 83, 66–88.

  23. Sun, K., Zheng, D.Z., Lu, Q. 2003. Splitting strategies for islanding operation of large-scale power systems using OBDD-based methods. IEEE Transactions on Power Systems 18, 912–923.

  24. Xu, L. 2012. Coordinated control of SVC and PSS for transient stability enhancement of multi-machine power system. TELKOMNIKA Indonesian Journal of Electrical Engineering 11, 1054–1062.

  25. Zare, H., Yaghobi, H., Alinejad-Beromi, Y. 2018. Adaptive concept of controlled islanding in power systems for wide-area out-of-step prediction of synchronous generators based on adaptive tripping index. IET Generation, Transmission and Distribution 12, 3829–3836.


ARTICLE INFORMATION

Received: 2022-01-28
Revised: 2022-06-30
Accepted: 2022-08-22
Available Online: 2022-11-28


Cite this article:

Samson, A.A., Popoola, O., Mbey, V. An alternative framework for implementing generator coherency prediction and islanding detection scheme considering critical contingency in an interconnected power grid. International Journal of Applied Science and Engineering, 19, 2022010. https://doi.org/10.6703/IJASE.202212_19(4).001

 

 

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Other people also read ...

doaj logo

 

2.3
2022CiteScore
 
 
48th percentile
Powered by  Scopus
 
 

SCImago Journal & Country Rank

IJASE - Most Read Articles

IJASE - Most popular articles