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access icon free Comparative performance assessment of a novel quasi-oppositional harmony search algorithm and internal model control method for automatic generation control of power systems

This initiative work addresses the comparative performance assessment of a novel quasi-oppositional harmony search (QOHS) algorithm and internal model control (IMC) method, in the environment of automatic generation control. These two techniques are applied to a single-area non-reheat and reheat turbine with and without droop characteristic, and four-area hydro-thermal interconnected power system under various operating conditions. Later on, robustness analysis of both the two test systems is carried out by varying the speed regulating parameters, time constants of governor, turbine, power system and the gain of power system in the range of ±50% in case of single-area test system. In four-area test system, the same is carried out with the consonance of step load perturbation in different control area at distinct time-interval. Simulation results show that the proposed QOHS algorithm offers better dynamic control with robust performance as compared with IMC based approach. For on-line, off-nominal operating conditions, fast acting Sugeno fuzzy logic (SFL) is applied to obtain on-line dynamic responses of the studied power system model. Moreover, time-domain simulation of the investigated four-area test system reveals that the proposed QOHS-SFL based intelligent controller yields on-line, off-nominal controller parameters, resulting in on-line optimal dynamic response profile.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
      • 31. Tizhoosh, H.R.: ‘Opposition-based learning: a new scheme for machine intelligence’. Proc. Int. Conf. Comput. Intell. Modeling Control and Autom., 2005, vol. 1, pp. 695701.
    12. 12)
      • 7. Moon, Y.H., Ryu, H.S., Choi, B.K., Kook, H.J.: ‘Improvement of system damping by using the differential feedback in the load frequency control’. Proc. IEEE PES, 1999, Winter Meeting, 1999, pp. 683688.
    13. 13)
      • 2. Bevrani, H.: ‘Intelligent automatic generation control’ (Springer, New York, 2009).
    14. 14)
    15. 15)
      • 1. Wood, A.J., Wollenberg, B.F.: ‘Power generation, operation and control’ (John Wiley & Sons, New York, 1996).
    16. 16)
      • 8. Poulin, E., Pomerleau, A.: ‘Unified PID design method based on a maximum peak resonance specification’, In: Proc. IEE Control Theory Appl., 1997, 144, pp. 566674.
    17. 17)
    18. 18)
    19. 19)
    20. 20)
    21. 21)
    22. 22)
    23. 23)
      • 27. Ogata, K.: ‘Modern control engineering’ (Printice Hall International, India, 1995, 2nd edn.).
    24. 24)
      • 29. Yang, X.S.: ‘Music-inspired harmony search algorithm-theory and applications’ (Springer, New York, 2009).
    25. 25)
      • 9. Khodabakhshian, A., Golbon, N.: ‘Robust load frequency controller design for hydro power systems’. Proc. IEEE CCA, 28–31 August 2005, pp. 15101515.
    26. 26)
    27. 27)
    28. 28)
    29. 29)
    30. 30)
      • 25. Rahnamayan, S., Tizhoosh, H.R., Salama, M.M.A.: ‘Quasi-oppositional differential evolution’. Proc. IEEE CEC, 2007, pp. 22292236.
    31. 31)
    32. 32)
    33. 33)
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