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access icon free Parallel-differential evolution approach for optimal event-driven load shedding against voltage collapse in power systems

Event-driven load shedding is an effective countermeasure against voltage collapse in power systems. Conventionally, its optimisation relies on sensitivity-based linear methods, which, however, could suffer from unrealistic assumptions and sub-optimality. In this study, an alternative approach based on parallel-differential evolution (P-DE) is proposed for efficiently and globally optimising the event-driven load shedding against voltage collapse. Working in a parallel structure, the approach consists of candidate buses selection, voltage stability assessment (VSA) and DE optimisation. Compared with conventional methods, it fully considers the non-linearity of the problem and is able to effectively escape from local optima and not limited to system modelling and unrealistic assumptions. Besides, any type of objective functions and VSA techniques can be used. The proposed approach has been tested on the IEEE 118-bus test system considering two cases for preventive control and corrective control, respectively, and compared with the two existing methods. Simulation results have verified its effectiveness and superiority over the compared methods.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
      • 8. Greene, S., Dobson, I., Alvarado, F.: ‘Sensitivity of the loading margin to voltage collapse with respect to arbitrary parameters’, IEEE Trans. Power Syst., 1997, 12, (1), pp. 262272 (doi: 10.1109/59.574947).
    17. 17)
      • 20. Han, J.W., Kamber, M.: ‘Data mining: concepts and techniques’ (Morgan Kaufmann Publishers, San Francisco, California, 2001).
    18. 18)
      • 22. Tasoulis, D.K., Pavlidis, N.G., Plagianakos, V.P., Vrahatis, M.N.: ‘Parallel differential evolution’. Proc. CEC 2004 Congress on Evolutionary Computation, 2004, vol. 2, pp. 20232029.
    19. 19)
      • 12. Wang, Y., Pordanjani, I., Xu, W.: ‘An event-driven demand response scheme for power system security enhancement’, IEEE Trans. Smart Grid, 2011, 2, (1), pp. 1117 (doi: 10.1109/TSG.2011.2105287).
    20. 20)
      • 11. Wang, Y., Pordanjani, I.R., Li, W., Xu, W., Vaahedi, E.: ‘Strategy to minimize the load shedding amount for voltage collapse prevention’, IET Gener. Transm. Distrib., 2011, 5, (3), pp. 307313 (doi: 10.1049/iet-gtd.2010.0341).
    21. 21)
      • 27. Zhang, R., Xu, Y., Dong, Z.Y., Luo, F., Wong, K.P.: ‘Voltage stability margin prediction by ensemble-based extreme learning machine’. Proc. 2013 IEEE PES General Meeting, Vancouver, CA, July 2013.
    22. 22)
      • 24. Xu, Y., Liu, S., Dong, Z.Y., Zhang, R., Koenig, M., Wigington, A.: ‘A hybrid model for forecasting time-varying reactive power load of power systems’. Proc. 17th Int. Conf. Intelligent System Applications to Power Systems (ISAP 2013), Tokyo, Japan, July 2013.
    23. 23)
      • 15. Vesterstrom, J., Thomsen, R.: ‘A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems’. Proc. IEEE Congress Evolutionary Computation, 2004, pp. 19801987.
    24. 24)
      • 30. MATLAB Optimization toolbox, http://www.mathworks.com.au/products/optimization/.
    25. 25)
      • 26. Van Cutsem, T., Kabouris, J., Christoforidis, G., Vournas, C.D.: ‘Application of real-time voltage security assessment to the Hellenic interconnected system’, IET Gener. Transm. Distrib., 2005, 152, (1), pp. 121131.
    26. 26)
      • 18. Xu, Y., Dong, Z.Y., Meng, K., Zhao, J.H., Wong, K.P.: ‘A hybrid method for transient stability constrained-optimal power flow computation’, IEEE Trans. Power Syst., 2012, 27, (4), pp. 17691777 (doi: 10.1109/TPWRS.2012.2190429).
    27. 27)
      • 3. Van Cutsem, T., Vournas, C.D.: ‘Emergency voltage stability controls: an overview’. Proc. IEEE PES General Meeting, Tampa, US, June 2007.
    28. 28)
      • 16. Yang, G.Y., Dong, Z.Y., Wong, K.P.: ‘A modified differential evolution algorithm with fitness sharing for power system planning’, IEEE Trans. Power Syst., 2008, 3, (2), pp. 514522 (doi: 10.1109/TPWRS.2008.919420).
    29. 29)
      • 19. Liang, C.H., Chung, C.Y., Wong, K.P., Duan, X.Z., Tse, C.T.: ‘Study of differential evolution for optimal reactive power flow’, IET Gener. Transm. Distrib., 2007, 1, (2), pp. 253260 (doi: 10.1049/iet-gtd:20060123).
    30. 30)
      • 10. Nikolaidis, V.C., Vournas, C.D.: ‘Design strategies for load-shedding schemes against voltage collapse in the Hellenic system’, IEEE Trans. Power Syst., 2008, 23, (2), pp. 582591 (doi: 10.1109/TPWRS.2008.919242).
    31. 31)
      • 2. Wang, Q., Ajjarapu, V.: ‘A critical review on preventive and corrective control against voltage collapse’, Electric Power Compon. Syst., 2001, 29, pp. 11331144 (doi: 10.1080/15325000151125694).
    32. 32)
      • 29. MPICH2, http://www.phase.hpcc.jp/mirrors/mpi/mpich2/.
    33. 33)
      • 14. Storn, R., Price, K.: ‘Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces’, J. Global Optim., 1997, 11, pp. 341359 (doi: 10.1023/A:1008202821328).
    34. 34)
      • 9. Feng, Z., Ajjarapu, V., Maratukulam, D.: ‘A comprehensive approach for preventive and corrective control to mitigate voltage collapse’, IEEE Trans. Power Syst., 2000, 15, (2), pp. 791797 (doi: 10.1109/59.867175).
    35. 35)
      • 31. Osman, A., Ammar, H.: ‘Dynamic load balancing strategies for parallel computers’. Int. Sym. Parallel and Distributed Computing (ISPDC), 2002.
    36. 36)
      • 7. Fang, Y.J., Xue, Y.: ‘An on-line pre-decision based transient stability control system for the Ertan power system’. Proc. Int. Conf. Power System Technology (POWERCON 2000), Perth, Australia, 2000.
    37. 37)
      • 17. Ceylan, O., Dag, H., Özdemir, A.: ‘Parallel contingency analysis using differential evolution based solution for branch outage problem’. Proc. Fifth Int. Conf. Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, (ICSCCW), September 2009, pp. 14.
    38. 38)
      • 5. Ladhani, S.S., Rosehart, W.: ‘Under voltage load shedding for voltage stability: overview of concepts and principles’. Proc. IEEE PES General Meeting, June 2004.
    39. 39)
      • 6. Dai, Y., Xu, Y., Dong, Z.Y., Wong, K.P., Zhuang, L.: ‘Real-time prediction of event-driven load shedding for frequency stability enhancement of power systems’, IET Gener. Transm. Distrib., 2012, 6, (9), pp. 914921 (doi: 10.1049/iet-gtd.2011.0810).
    40. 40)
      • 4. Xu, Y., Dai, Y., Dong, Z.Y., Xue, Y., Wong, K.P.: ‘Load shedding and its strategies against frequency instability in power systems’. Proc. IEEE PES General Meeting, San Diego, US, July 2012.
    41. 41)
      • 28. http://www.ee.washington.edu/research/pstca/.
    42. 42)
      • 1. Van Cutsem, T.: ‘Voltage instability: phenomena, countermeasures, and analysis methods’, Proc. IEEE, 2000, 88, (2), pp. 208227 (doi: 10.1109/5.823999).
    43. 43)
      • 21. Meng, K., Dong, Z.Y., Wong, K.P., Xu, Y., Luo, F.: ‘Speed-up the computing efficiency of power system simulator for engineering-based power system transient stability simulations’, IET Gener. Transm. Distrib., 2010, 4, (5), pp. 652661 (doi: 10.1049/iet-gtd.2009.0701).
    44. 44)
      • 23. Zhang, R., Dong, Z.Y., Xu, Y., Meng, K., Wong, K.P.: ‘Short-term load forecasting of Australian National Electricity Market by an ensemble model of extreme learning machine’, IET Gener. Transm. Distrib., 2013, 7, (4), pp. 391397 (doi: 10.1049/iet-gtd.2012.0541).
    45. 45)
      • 25. Ajjarapu, V., Christy, C.: ‘The continuation power flow: a tool for steady state voltage stability analysis’, IEEE Trans. Power Syst., 1992, 7, pp. 416423 (doi: 10.1109/59.141737).
    46. 46)
      • 13. Lee, K.Y., El-Sharkawi, M.A. (eds.): ‘Modern heuristic optimization techniques: theory and applications to power systems’ (IEEE and Wiley Press, 2008).
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