http://iet.metastore.ingenta.com
1887

Fractional-order lead-lag compensator-based multi-band power system stabiliser design using a hybrid dynamic GA-PSO algorithm

Fractional-order lead-lag compensator-based multi-band power system stabiliser design using a hybrid dynamic GA-PSO algorithm

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Power system stabilisers (PSSs) are supplementary controllers connected to the excitation system of synchronous generators to damp electromechanical oscillations. Multi-band PSSs are reported as advanced PSSs with the ability to damp out all oscillation modes present in the power systems. This study presents the design of a robust fractional-order multi-band power system stabiliser (Fo-MBPSS) using a meta-heuristic hybrid algorithm for dynamic stability improvement of multi-machine power systems. The large bandwidth, memory effect and flat phase contribution in the frequency response of fractional-order controllers are exploited to make the Fo-MBPSS perform well against a wide range of system uncertainties. The parameter tuning problem of Fo-MBPSS is transformed to an optimisation problem that is solved using a hybrid algorithm by combining a dynamic genetic algorithm (DGA) with a standard particle swarm optimisation (PSO) algorithm. The performance of the proposed DGA-PSO-Fo-MBPSS is evaluated through eigenvalue analysis, non-linear time-domain simulations and some performance indices, in two different multi-machine systems under different loading conditions and disturbances. The results are compared with PSO-based conventional MBPSS and PSO based Fo-MBPSS (PSO-Fo-MBPSS) to establish the fractional parameter effect on the improvement of the system dynamic response and the relevance of the proposed hybrid optimisation technique in achieving robustness.

References

    1. 1)
      • 1. Concordia, C., deMello, F.P.: ‘Concepts of synchronous machine stability as affected by excitation control’, IEEE Trans. Power Appar. Syst., 1969, 88, pp. 316329.
    2. 2)
      • 2. Larsen, E.V., Swann, D.: ‘Applying power system stabilizers Part I, II, III’, IEEE Trans. Power Appar. Syst., 1981, 100, pp. 30173041.
    3. 3)
      • 3. Abido, M.A.: ‘Robust design of multimachine power system stabilizers using simulated annealing’, IEEE Trans. Energy Convers., 2000, 15, (3), pp. 297304.
    4. 4)
      • 4. Abido, M.A.: ‘Optimal design of power-system stabilizers using particle swarm optimization’, IEEE Trans. Energy Convers., 2002, 17, pp. 406413.
    5. 5)
      • 5. Abido, M.A.: ‘Optimal multiobjective design of robust power system stabilizers using genetic algorithms’, IEEE Trans. Power Syst., 2003, 18, pp. 11251132.
    6. 6)
      • 6. Kuiava, R., Ramos, R.A., Britas, N.G.: ‘Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices’, IET Gener. Transm. Distrib., 2008, 3, pp. 919929.
    7. 7)
      • 7. Vakula, V.S., Sudha, K.R.: ‘Design of differential evolution algorithm-based robust fuzzy logic power system stabiliser using minimum rule base’, IET Gener. Transm. Distrib., 2012, 6, (2), pp. 121132, doi: 10.1049/iet-gtd.2011.0195.
    8. 8)
      • 8. Pahasa, J., Ngamroo, I.: ‘Adaptive power system stabilizer design using optimal support vector machines based on harmony search algorithm’, Electr. Power Compon. Syst., 2014, 42, (5), pp. 439452.
    9. 9)
      • 9. Peres, W., de Oliveira, E.J., Passos Filho, J.A., et al: ‘Coordinated tuning of power system stabilizers using bio-inspired algorithms’, Int. J. Electr. Power Energy Syst., 2015, 64, pp. 419428.
    10. 10)
      • 10. Lee, S., Park, J.K.: ‘Design of reduced-order observer-based variable structure power system stabiliser for unmeasurable state variables’, IEE Proc. Gener. Transm. Distrib., 1998, 145, pp. 1738.
    11. 11)
      • 11. Zhu, C., Khammash, M., Vittal, V., et al: ‘Robust power system stabilizer design using H loop shaping approach’, IEEE Trans. Power Syst., 2003, 18, pp. 810818.
    12. 12)
      • 12. Gupta, R., Bandyopadhyay, B., Kulkarni, A.: ‘Design of power system stabiliser for single-machine system using robust periodic output feedback controller’, IEE Proc. Gener. Transm. Distrib., 2003, 150, pp. 211216.
    13. 13)
      • 13. Sattar, K.: ‘Damping of low frequency power oscillations using improved pole-assignment controller’, Electr. Power Compon. Syst., 2006, 34, (2), pp. 233248.
    14. 14)
      • 14. Khodabakhshian, A., Hemmati, R.: ‘Robust decentralized multi-machine PSS design using quantitative feedback theory’, Int. J. Electr. Power Energy Syst., 2012, 41, pp. 112119.
    15. 15)
      • 15. Bandal, V., Bandyopadhyay, B.: ‘Robust decentralized output feedback sliding mode control technique-based power system stabilizer (PSS) for multimachine power system’, IET Control Theory Appl., 2007, 1, (5), pp. 15121522.
    16. 16)
      • 16. Hiyama, T., Kugimiya, M., Satoh, H.: ‘Advanced PID type fuzzy logic power system stabilizer’, IEEE Trans. Energy Convers., 1994, 9, (3), pp. 514520.
    17. 17)
      • 17. Anaparthi, K., Pal, B., El-Zobaidi, H.: ‘Coprime factorization approach in designing multi-input stabilizer for damping electromechanical oscillations in power systems’, IEEE Proc. Gener. Transm. Distrib., 2005, 152, pp. 301308.
    18. 18)
      • 18. Sumina, D., Buli'c, N.: ‘Three-dimensional power system stabilizer’, Electr. Power Syst. Res., 2010, 80, pp. 886892.
    19. 19)
      • 19. Kamwa, I., Grondin, R., Trudel, G.: ‘IEEE PSS2B versus PSS4B: the limits of performance of modern power system stabilizers’, IEEE Trans. Power Syst., 2005, 20, pp. 903915.
    20. 20)
      • 20. Rimorov, D., Joos, G, Kamwa, I.: ‘Model-based tuning approach for multi-band power system stabilisers PSS4B using an improved modal performance index’, IET Gener. Transm. Distrib., 2014, 9, (15), pp. 21352143.
    21. 21)
      • 21. Khodabakhshian, A., Hemmati, R., Moazzami, M.: ‘Multi-band power system stabilizer design by using CPCE algorithm for multi-machine power system’, Electr. Power Syst. Res., 2013, 101, pp. 3648.
    22. 22)
      • 22. Monje, C.A., Chen, Y.Q., Vinagre, B.M., et al: ‘Fractional-order systems and controls: fundamentals and applications’ (Springer, New York, NY, USA, 2010).
    23. 23)
      • 23. Pan, I., Das, S.: ‘Intelligent fractional order systems and control: an introduction’, Series: Studies in Computational Intelligence, vol. 438 (Springer-Verlag, Berlin, Germany, 2013).
    24. 24)
      • 24. Pan, I., Das, S.: ‘Frequency domain design of fractional order PID controller for AVR system using chaotic multi-objective optimization’, Int. J. Electr. Power Energy Syst., 2013, 51, pp. 106118.
    25. 25)
      • 25. Sondhi, S., Hote, Y.V.: ‘Fractional order PID controller for load frequency control’, Energy Convers. Manage., 2014, 85, pp. 343353. doi: 10.1016/j.enconman.2014.05.091.
    26. 26)
      • 26. Vikhram Yohanandhan, R., Srinivasan, L.: ‘Decentralised wide-area fractional order damping controller for a large-scale power system’, IET Gener. Transm. Distrib., 2016, 10, (5), pp. 11641178.
    27. 27)
      • 27. Tavazoei, M.S., Tavakoli-Kakhki, M.: ‘Compensation by fractional-order phase-lead/lag compensators’, IET Control Theory Appl., 2014, 8, (5), pp. 319329.
    28. 28)
      • 28. Petras, I.: ‘Stability of fractional-order systems with rational orders’, Fractional Calc. Appl. Anal., 2009, 12, (3), pp. 269298.
    29. 29)
      • 29. Anderson, P.M., Fouad, A.A.: ‘Power system control and stability’, (Wiley, Hoboken, NJ, USA, 2003, 2nd edn.).
    30. 30)
      • 30. Hong, T.P., Wang, H.S., Lin, W.Y., et al: ‘Evolution of appropriate crossover and mutation operators in a genetic process’, Appl. Intell., 2002, 16, (1), pp. 717.
    31. 31)
      • 31. Kim, D.H., Abraham, A., Hirota, K., et al: ‘Hybrid genetic: particle swarm optimization algorithm, hybrid evolutionary algorithms’ (Springer, Berlin Heidelberg, 2007), pp. 147170.
    32. 32)
      • 32. Hsu, Y.Y., Chen, C.L.: ‘Identification of optimum location for stabilizer applications using participation factors’, IEE Proc. C Gener. Trans. Distrib., 1987, 134, pp. 238244.
    33. 33)
      • 33. Pai, M.A.: ‘Energy function analysis for power system stability’ (Kluwer, Norwell, MA, 1989).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2017.1087
Loading

Related content

content/journals/10.1049/iet-gtd.2017.1087
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address