In this paper, a new criterion to quickly evaluate the system transient stability based on wide area measurement system (WAMS) information, energy function method and adjoint power system (APS) model is proposed. APS is a two-dimensional-first-order differential equation model, which can be considered as a virtual representation to the real power system. Meaning of APS is first explained by using the one machine infinite bus system. Then, a new criterion based on projection kinetic energy of APS is proposed to determine the transient stability of the original power system with multiple generators. Trajectory prediction method based on curve fitting technique is adopted to accelerate the evaluation process. The proposed method is sufficiently rapid since it does not rely on the network structure, system model, system parameters and the identification of the coherent generator groups. Therefore, it can be utilised for online transient stability assessment based on WAMS. Simulation results on the New England system and one of North China Power System validate the correctness and effectiveness of the proposed method.

References

1. 1)
  - 15. Kai, S., Lee, S.T.: ‘Power system security pattern recognition based on phase space visualization’. Proc. IEEE Int. Conf. Electric Utility Deregulation and Restructuring and Power Technologies (DRPT 2008), Nanjing, China, April 2008, pp. 964–969.
2. 2)
  - Y. Xue , T.V. Cutsem , M. Ribbens-Pavella . Extended equal area criterion justifications, generalizations, applications. IEEE Trans. Power Syst. , 1 , 44 - 52
3. 3)
  - 19. Gomez, F.R., Rajapakse, A.D., Annakkage, U.D., Fernando, I.T.: ‘Support vector machine based algorithm for post-fault transient stability status prediction using synchronized measurements’, IEEE Trans. Power Syst., 2011, 26, pp. 1474–1483 (doi: 10.1109/TPWRS.2010.2082575).
4. 4)
  - 9. Mariotto, L., Pinheiro, H., Cardoso, G., et al: ‘Power systems transient stability indices: an algorithm based on equivalent clusters of coherent generators’, IET Gener. Transm. Distrib., 2010, 4, (11), pp. 1223–1235 (doi: 10.1049/iet-gtd.2009.0647).
5. 5)
  - 3. Michel, A., Fouad, A., Vittal, V.: ‘Power system transient stability using individual machine energy functions’, IEEE Trans. Circuits Syst., 1983, 30, (5), pp. 266–276 (doi: 10.1109/TCS.1983.1085360).
6. 6)
  - 2. Watson, N.R., Arrillaga, J.: ‘Power systems electromagnetic transients simulation’ (IET, London, UK, 2003).
7. 7)
  - M. Pavella . Generalized one-machine equivalents in transient stability studies. IEEE Power Eng. Rev. , 50 - 52
8. 8)
  - 9. Qun, G., Rovnyak, S.M.: ‘Decision trees using synchronized phasor measurements for wide-area response-based control’, IEEE Trans. Power Syst., 2011, 26, (2), pp. 855–861 (doi: 10.1109/TPWRS.2010.2067229).
9. 9)
  - K.R. Padiya , S. Krishna . Online detection of loss of synchronism using energy function criterion. IEEE Trans. Power Deliv. , 1 , 46 - 55
10. 10)
  - 14. Kai, S., Lee, S.T., Pei, Z.: ‘An adaptive power system equivalent for real-time estimation of stability margin using phase-plane trajectories’, IEEE Trans. Power Syst., 2011, 26, (2), pp. 915–923 (doi: 10.1109/TPWRS.2010.2055900).
11. 11)
  - 4. Chiang, H.D., Wu, F.F., Varaiya, P.P.: ‘Foundations of the potential energy boundary surface method for power system transient stability analysis’, IEEE Trans. Circuits Syst., 1988, 35, (6), pp. 712–728 (doi: 10.1109/31.1808).
12. 12)
  - D.Z. Fang , T.S. Chung , Z. Yao , S. Wennan . Transient stability limit conditions analysis using a corrected transient energy function. IEEE Trans. Power Syst. , 804 - 810
13. 13)
  - 16. Liancheng, W., Girgis, A.A.: ‘A new method for power system transient instability detection’, IEEE Trans. Power Deliv., 1997, 12, (3), pp. 1082–1089 (doi: 10.1109/61.636874).
14. 14)
  - 27. Amraee, T., Ranjbar, S.: ‘Transient instability prediction using decision tree technique’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 3028–3037 (doi: 10.1109/TPWRS.2013.2238684).
15. 15)
  - 20. Fang, D.Z., Song, W., Zhang, Y.: ‘A new transient energy function’, Sci. China E, Technol. Sci., 2002, 45, (4), pp. 426–432.
16. 16)
  - 1. Kundur, P., Balu, N.J., Lauby, M.G.: ‘Power system stability and control’ (MCGraw-Hill, New York, USA, 1993).
17. 17)
  - 10. Hashiesh, F., Mostafa, H.E., Khatib, A.R., et al: ‘An intelligent wide area synchrophasor based system for predicting and mitigating transient instabilities’, IEEE Trans. Smart Grid, 2012, 3, (2), pp. 645–652 (doi: 10.1109/TSG.2012.2187220).
18. 18)
  - 22. Pai, M.A.: ‘Energy function analysis for power system stability’ (Kluwer Academic Publishers, Norwell, MA, USA, 1989).
19. 19)
  - 11. Hashiesh, F., Mostafa, H.E., Mansour, M.M., et al: ‘Wide area transient stability prediction using on-line artificial neural networks’. Proc. Electric Power Conf., Vancouver, BC, Canada, October 2008, pp. 1–7.
20. 20)
  - D.Z. Fang , J.G. Yang , W. Sun . Transient stability assessment using projection formulations. IET Gener. Transm. Distrib. , 6 , 596 - 603
21. 21)
  - J. De La Ree , V. Centeno , J.S. Thorp , A.G. Phadke . Synchronized phasor measurement applications in power systems. IEEE Trans. Smart Grid , 1 , 20 - 27
22. 22)
  - 15. Paudyal, S., Ramakrishna, G., Sachdev, M.S.: ‘Application of equal area criterion conditions in the time domain for out-of-step protection’, IEEE Trans. Power Deliv., 2010, 25, (4), pp. 600–609 (doi: 10.1109/TPWRD.2009.2032326).

Criterion to evaluate power system online transient stability based on adjoint system energy function

References

Related content