Generation rejection scheme based on a combinational rotor angle trajectory prediction

Document Type : Article

Authors

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

Abstract

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.

Keywords

References

REFRENCES:

[1]    H. Goh, K. Chen, F. Crocker, K. Iskandar,  et al.: 'A review on equipment protection and system protection relay in power system'. International Journal of Integrated Engineering, 2017, vol. 9. pp.7-12.
[2] K. Shafeeque Ahmed, Sh. Prabhakar Karthikeya, S. Sahoo.: ' Special Protection Schemes: A Survey and Vision for the Future'. Applied Mechanics and Materials, 2016, vol. 839, pp. 49-53.
[3] IR, Pordanjani, HA. Abyaneh, SHH. Sadeghi, et al.: 'Risk reduction in special protection systems by using an online method for transient instability prediction'. International Journal of Electrical Power & Energy Systems, 2010, vol. 2, pp. 156–62.
[4] Daham Min,  Seog-Joo Kim,  Sangsoo Seo,  et al.: 'Computing safety margins of a generation rejection scheme: A framework for online implementation'. IEEE Trans. Smart Grid, 2018, vol. 9, no. 3, pp. 2337-2346.
[5] G. G. Karady and G. Jun.: 'A hybrid method for generator tripping'. IEEE Trans. Power Systems, 2002, vol. 17, pp. 1102-1107.
[6] F. Aminifa, A. Safdarian, M. Fotuhi-Firuzabad, et al.: 'A Multi-Objective Framework for Enhancing the Reliability and Minimizing the Cost of PMU Deployment in Power Systems'. Scientia Iranica, 2016, vol 6, pp. 2917-2927.
[7] Khandani. A , Akbari Forou. A.: ‘Providing transient stability by excitation system response improvement methods through long-term contracts'. Scientia Iranica, 2019, vol. 26, no.3, pp. 1652-1663.
[8] W. Xiaochen, Z. Jinquan, X. Aidong, 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, 2011, pp. 320-326.
[9] D. Choi, S. H. Lee, Y. C. Kang, et al.: 'Analysis on special protection scheme of korea electric power system by fully utilizing STATCOM in a generation side'. IEEE Trans. Power Systems, 2017, vol. 32, no. 3, pp. 1882-1890.
[10] T. Weckesser, H. Jóhannsson, and J. Østergaard.: 'Real-time remedial action against aperiodic small signal rotor angle instability'. IEEE Trans. Power Systems, 2016, vol. 31, no. 1, pp. 387-396.
[11] H. Yang, W. Zhang, F. Shi, et al.: 'PMU-based model-free method for transient instability prediction and emergency generator-shedding control'. International Journal of Electrical Power & Energy Systems.2019, vol 105, pp. 381-393.
[12] M. Esmaili, A. A. Hajnoroozi, and H. A. Shayanfar.: 'Risk evaluation of online special protection systems'. International Journal of Electrical Power & Energy Systems, 2012, vol. 41, pp. 137-144.
[13] C. W. Liu and J. Thorp.: 'Application of synchronised phasor   measurements to real-time transient stability prediction'. IEE Proceedings - Generation, Transmission and Distribution,1995,  vol. 142, pp. 355-360.
[14]  AD. Rajapakse, F. Gomez, K. Nanayakkara, et al.: 'Rotor angle instability prediction using post-disturbance voltage trajectories'. IEEE Trans. Power Systems, 2010, vol. 25(2), pp. 947–56.
[15] N. G. Bretas and A. G. Phadke.: 'Real time instability prediction through adaptive time series coefficients'. Power Engineering Society Winter Meeting, IEEE, 1999, vol.1, pp. 731-736.
[16] Salimian, Mohammad Reza, and Mohammad Reza Aghamohammadi.: '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 2016, no. 4, pp. 2488-2497.
[17] Kamali, Sadegh, Turaj Amraee, and Seyed Mohammad Taghi Bathaee.: 'Prediction of unplanned islanding using an energy based strategy'. IET Generation, Transmission & Distribution, 2016, no. 1, pp. 183-191.
[18]  M. Zima.: 'Special protection schemes in electric power systems'. EEH-Power Systems Laboratory, 2002, pp. 1-22.
[19]  F. Weihui, Z. Sanyi, J. D. McCalley, et al.: 'Risk assessment for special protection systems'. IEEE Trans. Power Systems, 2002, vol. 17, pp. 63-72.
[20]  P. Kundur.: 'Power System Stability & Control.' 2005, 5th  Reprint, Tata McGraw-Hill, New Delhi.
[21] S. Teimourzadeh, M. Davarpanah, F. Aminifar, et al.: 'An Adaptive Auto-Reclosing Scheme to Preserve Transient Stability of Microgrids'. IEEE Trans. Smart Grid,2016,  vol. 9, no. 4, pp. 2638-2646.
[22] A. A. Hajnoroozi, F. Aminifar, and H. Ayoubzadeh.:'Generating unit model validation and calibration through synchrophasor measurements', IEEE Transactions on Smart Grid, 2015, vol. 6, pp. 441-449.
[23] DIgSILENT PowerFactory, available at:/http://www.digsilent.de/.
Scientia Iranica
Volume 28, Special issue on collective behavior of nonlinear dynamical networks
Transactions on Computer Science & Engineering and Electrical Engineering (D)
June 2021
Pages 1579-1591

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History

  • Receive Date: 29 July 2019
  • Revise Date: 05 October 2019
  • Accept Date: 22 December 2019

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