Generation rejection scheme based on a combinational rotor angle trajectory prediction

Document Type : Article


1 Centre of Excellence for Power System Automation and Operation, Iran University of Science and Technology, Tehran, Iran

2 School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran


This paper presents a response-based generating rejection scheme (GRS) based on an angular stability prediction logic to initiate the outage of accelerated generating units while saving the rest of generating units from the loss of synchronism. First trigonometric, polynomial, and hybrid models of rotor angle trajectory based on the reasonable assumptions are proofed. Then, by taking these models in the prediction step, through the maximum use of measured data based on defining the forecast horizon (FH) and data window with incremental length, the stability/instability of generating units is separately predicted. Next, the status of tripping signal based on a combinational logic of the output results of the angular stability prediction method is specified. In the developed logic, if at least two models of the three designated models yield the same response about the unit stability status, the trip signal is accordingly fired or blocked. The proposed method is examined on the one machine infinite bus and the WSCC standard test bed under different operation and fault scenarios. The obtained results demonstrate that beside simplicity, low computational burden, and very short processing time, the proposed combinatorial method outperforms the existing ones working with individual prediction models.


1. Goh, H., Chen, K., Crocker, F., et al. A review   on equipment protection and system protection relay   in power system", International Journal of Integrated   Engineering, 9, pp. 7{12 (2017).   2. Shafeeque Ahmed, K., Prabhakar Karthikeya, Sh.,   and Sahoo, S. Special protection schemes: A survey   and vision for the future", Applied Mechanics and   Materials, 839, pp. 49{53 (2016).   3. Pordanjani, I.R., Abyaneh, H.A., Sadeghi, S.H.H.,   et al. Risk reduction in special protection systems   by using an online method for transient instability   prediction", International Journal of Electrical Power   & Energy Systems, 2, pp. 156{62 (2010).   4. Daham, M., Seog-Joo, K., Sangsoo, S., et al. Computing   safety margins of a generation rejection scheme: A   framework for online implementation", IEEE Trans.   Smart Grid, 9(3), pp. 2337{2346 (2018).   5. Karady, G.G. and Jun, G. A hybrid method for   generator tripping", IEEE Trans. Power Systems, 17,   pp. 1102{1107 (2002).   6. Aminifar, F., Safdarian, A., Fotuhi-Firuzabad, M., et   al. A multi-objective framework for enhancing the   reliability and minimizing the cost of PMU deployment   in power systems", Scientia Iranica, 6, pp. 2917{2927   (2016).   7. Khandani, A. and Akbari Forou, A. Providing transient   stability by excitation system response improvement   methods through long-term contracts", Scientia   Iranica, 26(3), pp. 1652{1663 (2019).   8. Xiaochen, W., Jinquan, Z., Aidong, X., et al. Review   on transient stability prediction methods based on real   time wide-area phasor measurements", Electric Utility   Deregulation and Restructuring and Power Technologies   (DRPT), 4th International Conference, pp. 320{   326 (2011).   9. Choi, D., Lee, S.H., Kang, Y.C., et al. Analysis   on special protection scheme of Korea electric power   system by fully utilizing STATCOM in a generation   side", IEEE Trans. Power Systems, 32(3), pp. 1882{   1890 (2017).   10. Weckesser, T., J_ohannsson, H., and _stergaard, J.   Real-time remedial action against aperiodic small   signal rotor angle instability", IEEE Trans. Power   Systems, 31(1), pp. 387{396 (2016).   11. Yang, H., Zhang, W., Shi, F., et al. PMU-based   model-free method for transient instability prediction   and emergency generator-shedding control", International   Journal of Electrical Power & Energy Systems,   105, pp. 381{393 (2019).   12. Esmaili, M., Hajnoroozi, A.A., and Shayanfar, H.A.   Risk evaluation of online special protection systems",   International Journal of Electrical Power & Energy   Systems, 41, pp. 137{144 (2012).   13. Liu, C.W. and Thorp, J. Application of synchronised   phasor measurements to real-time transient stability   prediction", IEE Proceedings - Generation, Transmission   and Distribution, 142, pp. 355{360 (1995).   14. Rajapakse, A.D., Gomez, F., Nanayakkara, K., et   al. Rotor angle instability prediction using postdisturbance   voltage trajectories", IEEE Trans. Power   Systems, 25(2), pp. 947{56 (2010).   15. Bretas, N.G. and Phadke, A.G. Real time instability   prediction through adaptive time series coe_cients",   Power Engineering Society Winter Meeting, IEEE, 1,   pp. 731{736 (1999).   16. Salimian, M.R. and Aghamohammadi, M.R. Intelligent   out of step predictor for inter area oscillations   using speed-acceleration criterion as a time matching   for controlled islanding", IEEE Transactions on Smart   Grid, 4, pp. 2488{2497 (2016).   17. Kamali, S., Amraee, T., and Bathaee, S.M.T. Prediction   of unplanned islanding using an energy based   strategy", IET Generation, Transmission & Distribution,   1, pp. 183{191 (2016).   18. Zima, M., Special Protection Schemes in Electric   Power Systems, EEH-Power Systems Laboratory, pp.   1{22 (2002).   19. Weihui, F., Sanyi, Z., McCalley, J.D., et al. Risk assessment   for special protection systems", IEEE Trans.   Power Systems, 17, pp. 63{72 (2002).   20. Kundur, P. Power System Stability & Control, 5th   Reprint, Tata McGraw-Hill, New Delhi (2005).   A.A. Hajnorouzi et al./Scientia Iranica, Transactions D: Computer Science & ... 28 (2021) 1579{1591 1591   21. Teimourzadeh, S., Davarpanah, M., Aminifar, F., et   al. An adaptive auto-reclosing scheme to preserve   transient stability of microgrids", IEEE Trans. Smart   Grid, 9(4), pp. 2638{2646 (2016).   22. Hajnoroozi, A.A., Aminifar, F., and Ayoubzadeh,   H. Generating unit model validation and calibration   through synchrophasor measurements", IEEE Transactions   on Smart Grid, 6, pp. 441{449 (2015).   23. DIgSILENT PowerFactory, available at:/http://www.